Visualizing data with Python - NICAR16.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing data with Python\n",
    "\n",
    "This is a tutorial for making simple exploratory and publication-grade charts using Matplotlib and pandas.\n",
    "\n",
    "First, let's load matplotlib's pyplot module."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# This Jupyter magic function will draw our charts right into the notebook\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matplotlib takes in data as lists. Let's make the simplest chart possible using a small list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1062951d0>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Lmt0O0ePGiNyl1auTQr18uXT33fSp8UpDQ/mc5V3W7HaIwo2XNfvUzY9mn3rWLGnmTPrU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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106165350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = [3,6,8,12,4,24]\n",
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you only feed Matplotlib one list, it will assume the numbers are on the y axis. It will generate an x axis with the index of each y value. Let's give it x values now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1062cf190>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5Sf56mZe1djxGjhzD4i6tWRMC94oV0gMPkOfG31q1Kp+9zMtaOx4jkGNAzTx389bMc8+Y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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x104976d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [10, 20, 30, 40, 50, 60]\n",
    "plt.plot(x, data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, when you pass in two lists, the x axis values must come first. \n",
    "\n",
    "Now this chart isn't very informative. Let's give it a title and axis labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x106504bd0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FAF0RMTYi3pVta+q5+BFwTURsSvp/8hCDPRcRUfoPMAa4L/f8IWDd7PFo4KGy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\nwMyswZwEzMwazEnAzKzB/j/HfpJu4KSyfgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106319ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, data)\n",
    "plt.title(\"Python skills over time\")\n",
    "plt.xlabel(\"Days of study\")\n",
    "plt.ylabel(\"Skill level\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You know what, these charts are pretty ugly. Thankfully, Matplotlib comes with a few preset styles. Let's list them all."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[u'dark_background', u'bmh', u'grayscale', u'ggplot', u'fivethirtyeight']\n"
     ]
    }
   ],
   "source": [
    "print plt.style.available"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I like the FiveThirtyEight style. Let's use that. But I want a dotted red line instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x106319a90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fdlSIQgjh9DyOH8d7505uhYSQUKmS1uEQEBCQ69fafQUXHBxM2bJlCQkJoUeP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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106618490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "plt.plot(x, data, 'r--')  # Adds marker color and style\n",
    "plt.title(\"Python skills over time\")\n",
    "plt.xlabel(\"Days of study\")\n",
    "plt.ylabel(\"Skill level\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Actually, I think I prefer green squares."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x106756810>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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REVF1URpwHh4eau+Mk0yIiKi2UBpw+/fvf5t1EBERVSulAdevX7+3WQcREVG1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\nR0REgsSAIyIiQfp/db7nxqk0zuEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1066d1390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, data, 'gs')\n",
    "plt.title(\"Python skills over time\")\n",
    "plt.xlabel(\"Days of study\")\n",
    "plt.ylabel(\"Skill level\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's a [handy reference](http://matplotlib.org/api/markers_api.html) for all the possible markers you can use in Matplotlib.\n",
    "But now some of the points are outside the chart limits. So let's fix our limits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10680b0d0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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heZnuvygiIpBDgJ07d+6hNujp6Znrtk8++SRPPvkkACNGjMi0Pj09nRIlSuDm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\nSQEmIiJ2SQEmIiJ2SQEmIiJ26f8DU+eLCF2PCCAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10677c6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, data, 'gs')\n",
    "plt.xlim(5, 65) # lowest and highest values on the scale\n",
    "plt.ylim(0, 30)\n",
    "plt.title(\"Python skills over time\")\n",
    "plt.xlabel(\"Days of study\")\n",
    "plt.ylabel(\"Skill level\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That drop on the 50th day? It stands out. Let's explain it with an annotation. And let's go back to a blue line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x106a3fed0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WrFhBq1atsLe35+7du1y8eJGzZ88SEBBQIENqXbp0YcmSJcyePZvz58/rvlAZGuotLMOG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\nAv+tAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10691a110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, data, 'b-')\n",
    "plt.xlim(5, 65)\n",
    "plt.ylim(0, 30)\n",
    "plt.title(\"Python skills over time\")\n",
    "plt.xlabel(\"Days of study\")\n",
    "plt.ylabel(\"Skill level\")\n",
    "plt.text(45, 2, \"I was drunk\")  # x position, y position, text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OK, so we can make pretty annotated line charts with fake data. Wahoo. What we really want is to load in real data and get insights out of it. For this, we'll use pandas, a powerful data analysis library that's very good at importing data from text files, like a CSV.\n",
    "\n",
    "Let's load in some data on the emissions of air pollutants by businesses in Colorado. [Source: EPA](http://www3.epa.gov/airquality/airdata/ad_data.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Facility Name</th>\n",
       "      <th>Facility Address</th>\n",
       "      <th>Nitrogen Oxides</th>\n",
       "      <th>PM10</th>\n",
       "      <th>PM2.5</th>\n",
       "      <th>Volatile Organic Compounds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>.PETROLEUM DEV - SATER 11; 12; 21; 22-19</td>\n",
       "      <td>NW NW SEC 19 T4N R63W</td>\n",
       "      <td>1.759880</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.231880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1111 TOWER - FOUR SEASONS HOTEL</td>\n",
       "      <td>1111 14th St</td>\n",
       "      <td>7.730300</td>\n",
       "      <td>0.354318</td>\n",
       "      <td>0.354318</td>\n",
       "      <td>0.354318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31ST ST</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>188.416000</td>\n",
       "      <td>4.942880</td>\n",
       "      <td>4.794590</td>\n",
       "      <td>12.031100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36TH ST</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>159.948000</td>\n",
       "      <td>4.402070</td>\n",
       "      <td>4.270010</td>\n",
       "      <td>10.755400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>910 GENERATION COMPANY</td>\n",
       "      <td>910 15TH ST STE 1050</td>\n",
       "      <td>11.160000</td>\n",
       "      <td>0.455400</td>\n",
       "      <td>0.435309</td>\n",
       "      <td>1.569100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>A &amp; S CONSTRUCTION CO. - ASPHALT</td>\n",
       "      <td>6200 COUNTY ROAD 107</td>\n",
       "      <td>8.150060</td>\n",
       "      <td>0.976910</td>\n",
       "      <td>0.413866</td>\n",
       "      <td>5.879524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ABSMEIER LANDSCAPING  - MALOUFF</td>\n",
       "      <td>NE NE SEC 4 T36N R8E</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>1.048201</td>\n",
       "      <td>0.415919</td>\n",
       "      <td>0.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ACA PRODUCTS; INC.</td>\n",
       "      <td>AVERY PIT</td>\n",
       "      <td>0.152334</td>\n",
       "      <td>12.418902</td>\n",
       "      <td>4.019908</td>\n",
       "      <td>0.217955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ACH FOAM TECHNOLOGIES-EPS PRODUCTS</td>\n",
       "      <td>5250 SHERMAN ST</td>\n",
       "      <td>2.720000</td>\n",
       "      <td>0.209200</td>\n",
       "      <td>0.174770</td>\n",
       "      <td>92.740000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ACME BRICK COMPANY</td>\n",
       "      <td>401 PRAIRIE HAWK DR</td>\n",
       "      <td>26.676000</td>\n",
       "      <td>11.758967</td>\n",
       "      <td>7.946095</td>\n",
       "      <td>3.045000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Facility Name       Facility Address  \\\n",
       "0  .PETROLEUM DEV - SATER 11; 12; 21; 22-19  NW NW SEC 19 T4N R63W   \n",
       "1           1111 TOWER - FOUR SEASONS HOTEL           1111 14th St   \n",
       "2                                   31ST ST                Unknown   \n",
       "3                                   36TH ST                Unknown   \n",
       "4                    910 GENERATION COMPANY   910 15TH ST STE 1050   \n",
       "5          A & S CONSTRUCTION CO. - ASPHALT   6200 COUNTY ROAD 107   \n",
       "6           ABSMEIER LANDSCAPING  - MALOUFF   NE NE SEC 4 T36N R8E   \n",
       "7                        ACA PRODUCTS; INC.              AVERY PIT   \n",
       "8        ACH FOAM TECHNOLOGIES-EPS PRODUCTS        5250 SHERMAN ST   \n",
       "9                        ACME BRICK COMPANY    401 PRAIRIE HAWK DR   \n",
       "\n",
       "   Nitrogen Oxides       PM10     PM2.5  Volatile Organic Compounds  \n",
       "0         1.759880   0.010000  0.010000                    1.231880  \n",
       "1         7.730300   0.354318  0.354318                    0.354318  \n",
       "2       188.416000   4.942880  4.794590                   12.031100  \n",
       "3       159.948000   4.402070  4.270010                   10.755400  \n",
       "4        11.160000   0.455400  0.435309                    1.569100  \n",
       "5         8.150060   0.976910  0.413866                    5.879524  \n",
       "6         0.400000   1.048201  0.415919                    0.050000  \n",
       "7         0.152334  12.418902  4.019908                    0.217955  \n",
       "8         2.720000   0.209200  0.174770                   92.740000  \n",
       "9        26.676000  11.758967  7.946095                    3.045000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Load file into a pandas data frame and print the first 10 rows\n",
    "df = pd.read_csv(\"co_air_quality.csv\")\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas neatly loaded up the data and diplays it in a nice table format in the Jupyter notebook.\n",
    "\n",
    "The data we're using here has been prepared and is ready for action. In the real world, you may need to clean and reshape the data to make it usable. Pandas is good for that, too.\n",
    "\n",
    "Now let's rename our columns so we can use them more conveniently."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>address</th>\n",
       "      <th>NOx</th>\n",
       "      <th>PM10</th>\n",
       "      <th>PM25</th>\n",
       "      <th>VOC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>.PETROLEUM DEV - SATER 11; 12; 21; 22-19</td>\n",
       "      <td>NW NW SEC 19 T4N R63W</td>\n",
       "      <td>1.75988</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.231880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1111 TOWER - FOUR SEASONS HOTEL</td>\n",
       "      <td>1111 14th St</td>\n",
       "      <td>7.73030</td>\n",
       "      <td>0.354318</td>\n",
       "      <td>0.354318</td>\n",
       "      <td>0.354318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31ST ST</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>188.41600</td>\n",
       "      <td>4.942880</td>\n",
       "      <td>4.794590</td>\n",
       "      <td>12.031100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36TH ST</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>159.94800</td>\n",
       "      <td>4.402070</td>\n",
       "      <td>4.270010</td>\n",
       "      <td>10.755400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>910 GENERATION COMPANY</td>\n",
       "      <td>910 15TH ST STE 1050</td>\n",
       "      <td>11.16000</td>\n",
       "      <td>0.455400</td>\n",
       "      <td>0.435309</td>\n",
       "      <td>1.569100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       name                address        NOx  \\\n",
       "0  .PETROLEUM DEV - SATER 11; 12; 21; 22-19  NW NW SEC 19 T4N R63W    1.75988   \n",
       "1           1111 TOWER - FOUR SEASONS HOTEL           1111 14th St    7.73030   \n",
       "2                                   31ST ST                Unknown  188.41600   \n",
       "3                                   36TH ST                Unknown  159.94800   \n",
       "4                    910 GENERATION COMPANY   910 15TH ST STE 1050   11.16000   \n",
       "\n",
       "       PM10      PM25        VOC  \n",
       "0  0.010000  0.010000   1.231880  \n",
       "1  0.354318  0.354318   0.354318  \n",
       "2  4.942880  4.794590  12.031100  \n",
       "3  4.402070  4.270010  10.755400  \n",
       "4  0.455400  0.435309   1.569100  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = [\"name\", \"address\", \"NOx\", \"PM10\", \"PM25\", \"VOC\"]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can pass in a column to matplotlib and it will behave like a list (officially, a column, or any one-dimensional sequence of data, is called a **Series** in pandas). \n",
    "\n",
    "A column can be called with dot notation, e.g. `df.column` or as a dictionary lookup, e.g. `df['column']`.\n",
    "\n",
    "Let's look at a histogram of VOCs divided into 20 bins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  1.72200000e+03,   9.50000000e+01,   3.50000000e+01,\n",
       "          1.30000000e+01,   7.00000000e+00,   4.00000000e+00,\n",
       "          5.00000000e+00,   3.00000000e+00,   0.00000000e+00,\n",
       "          3.00000000e+00,   1.00000000e+00,   0.00000000e+00,\n",
       "          0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
       "          0.00000000e+00,   1.00000000e+00,   1.00000000e+00,\n",
       "          0.00000000e+00,   1.00000000e+00]),\n",
       " array([  1.20000000e-05,   3.49435885e+01,   6.98871649e+01,\n",
       "          1.04830741e+02,   1.39774318e+02,   1.74717894e+02,\n",
       "          2.09661471e+02,   2.44605047e+02,   2.79548624e+02,\n",
       "          3.14492200e+02,   3.49435777e+02,   3.84379353e+02,\n",
       "          4.19322929e+02,   4.54266506e+02,   4.89210082e+02,\n",
       "          5.24153659e+02,   5.59097235e+02,   5.94040812e+02,\n",
       "          6.28984388e+02,   6.63927965e+02,   6.98871541e+02]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5uS5evMiSJUtoa2vj5Zdf/tZ5r9cbjB8bEI+nh8bGRrq7u/t7KT4NDQ39vYQ+YcRcRswE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10671d5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df.VOC, bins=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the vast majority of records are in the lower end of emissions, between 0 and 30. But there are a few heavy polluters. Let's see the distribution of the data another way, as a box plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'boxes': [<matplotlib.lines.Line2D at 0x108d80610>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x108d8f4d0>,\n",
       "  <matplotlib.lines.Line2D at 0x108d8fb10>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x108d9c7d0>],\n",
       " 'means': [],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x108d9c190>],\n",
       " 'whiskers': [<matplotlib.lines.Line2D at 0x108d80790>,\n",
       "  <matplotlib.lines.Line2D at 0x108d80e50>]}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3BC5wXKYDABhHGAEGzZ/fa7oEYEwgjACDCCMggjACABhHGAEAjCOMAIO46RWIIIwAg15+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\nwDjCCABg3P8D/d6Gsg7oC1MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108b24a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(df.VOC)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The average value (long black line) is quite low, but the highest values are pretty huge, comparatively. \n",
    "\n",
    "Let's compare the boxplots of all the pollutants in the data. If we want to see charts side-by-side, matplotlib lets us create subplots in the same canvas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1091441d0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EBBwcHJg6dSqFhYUMHTqUFStWaF6YlNO/fx7gVGmcNC8HDx7k7rvvBi5/6UtISCAhIYGJ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\neJGCLxEREREv+j9O4nicjZhKaQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108dba790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First, create the canvas for the four charts. Let's make it big, 9 x 6 inches.\n",
    "fig = plt.figure(figsize=[9, 6])\n",
    "\n",
    "# Then create the subplots. \n",
    "# The three numbers you pass to add_subplot are: number of rows, number of columns,\n",
    "# and which plot in this grid you're defining. So 221 means a canvas with two across, \n",
    "# two down, specifying the top-left (1) subplot. \n",
    "ax1 = fig.add_subplot(221)\n",
    "ax2 = fig.add_subplot(222)\n",
    "ax3 = fig.add_subplot(223)\n",
    "ax4 = fig.add_subplot(224)\n",
    "\n",
    "# Now call the plot for each and set their titles.\n",
    "\n",
    "ax1.boxplot(df.VOC)\n",
    "ax1.set_title(\"VOC\")\n",
    "\n",
    "ax2.boxplot(df.NOx)\n",
    "ax2.set_title(\"NOx\")\n",
    "\n",
    "ax3.boxplot(df.PM25)\n",
    "ax3.set_title(\"PM2.5\")\n",
    "\n",
    "ax4.boxplot(df.PM10)\n",
    "ax4.set_title(\"PM10\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar distributions across all pollutants. \n",
    "\n",
    "Notice that instead of calling `title` on the plot, we called `set_title`. That's because we are now adding a title to a plot instance instead of matplotlib (plt) itself. This gives us a lot more customizing power, which you'll see later on.\n",
    "\n",
    "Now let's make a bar chart of the top 10 VOC and PM2.5 pollutants. First, we'll make a new pandas data frame for each chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>VOC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1841</th>\n",
       "      <td>WPX ENERGY LLC - PARACHUTE WMF</td>\n",
       "      <td>698.871541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>Denver Intl</td>\n",
       "      <td>625.585141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1123</th>\n",
       "      <td>MILLERCOORS; LLC - GOLDEN BREWERY</td>\n",
       "      <td>570.930000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>COLORADO INTERSTATE GAS CO  CHEYENNE STN</td>\n",
       "      <td>350.370000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1840</th>\n",
       "      <td>WPX ENERGY - RULISON WATER MANAGEMENT</td>\n",
       "      <td>320.154475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>ENTERPRISE GAS PROC - MEEKER GAS PLANT</td>\n",
       "      <td>317.662263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1648</th>\n",
       "      <td>SUNCOR ENERGY - DENVER REFINERY</td>\n",
       "      <td>315.179760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>KMCGEE FT LUPTON/PLATTE VALLEY/LANCASTER</td>\n",
       "      <td>276.600380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653</th>\n",
       "      <td>ENCANA OIL &amp; GAS - HIGH MESA COMP STATIO</td>\n",
       "      <td>262.566680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1111</th>\n",
       "      <td>METAL CONTAINER CORP</td>\n",
       "      <td>245.766000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          name         VOC\n",
       "1841            WPX ENERGY LLC - PARACHUTE WMF  698.871541\n",
       "554                                Denver Intl  625.585141\n",
       "1123         MILLERCOORS; LLC - GOLDEN BREWERY  570.930000\n",
       "415   COLORADO INTERSTATE GAS CO  CHEYENNE STN  350.370000\n",
       "1840     WPX ENERGY - RULISON WATER MANAGEMENT  320.154475\n",
       "693     ENTERPRISE GAS PROC - MEEKER GAS PLANT  317.662263\n",
       "1648           SUNCOR ENERGY - DENVER REFINERY  315.179760\n",
       "976   KMCGEE FT LUPTON/PLATTE VALLEY/LANCASTER  276.600380\n",
       "653   ENCANA OIL & GAS - HIGH MESA COMP STATIO  262.566680\n",
       "1111                      METAL CONTAINER CORP  245.766000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Take only the name and VOC columns, sort descending by VOC and take the top 10 rows.\n",
    "# Note that when taking multiple columns, the dictionary lookup notation must be used.\n",
    "top_VOC = df[[\"name\", \"VOC\"]].sort(\"VOC\", ascending=False).head(10)\n",
    "top_VOC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>PM25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1519</th>\n",
       "      <td>ROCKY MOUNTAIN ARSENAL USARMY / FRALEY</td>\n",
       "      <td>647.144264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1787</th>\n",
       "      <td>WASTE MANAGEMENT OF COLORADO-DEN/ARAP DI</td>\n",
       "      <td>451.407938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>CRIPPLE CREEK &amp; VICTOR GOLD MINING CO</td>\n",
       "      <td>350.092309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1648</th>\n",
       "      <td>SUNCOR ENERGY - DENVER REFINERY</td>\n",
       "      <td>240.506849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1373</th>\n",
       "      <td>PLATTE RIVER POWER AUTHORITY - RAWHIDE</td>\n",
       "      <td>173.100294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1421</th>\n",
       "      <td>PUBLIC SERVICE CO CHEROKEE PLT</td>\n",
       "      <td>171.971395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>TRI STATE GENERATION CRAIG</td>\n",
       "      <td>158.842837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>CF &amp; I STEEL L P</td>\n",
       "      <td>118.277914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1429</th>\n",
       "      <td>PUBLIC SERVICE CO HAYDEN PLT</td>\n",
       "      <td>106.690409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1255</th>\n",
       "      <td>OWENS-BROCKWAY GLASS CONTAINER INC.</td>\n",
       "      <td>98.664760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          name        PM25\n",
       "1519    ROCKY MOUNTAIN ARSENAL USARMY / FRALEY  647.144264\n",
       "1787  WASTE MANAGEMENT OF COLORADO-DEN/ARAP DI  451.407938\n",
       "483      CRIPPLE CREEK & VICTOR GOLD MINING CO  350.092309\n",
       "1648           SUNCOR ENERGY - DENVER REFINERY  240.506849\n",
       "1373    PLATTE RIVER POWER AUTHORITY - RAWHIDE  173.100294\n",
       "1421            PUBLIC SERVICE CO CHEROKEE PLT  171.971395\n",
       "1714                TRI STATE GENERATION CRAIG  158.842837\n",
       "281                           CF & I STEEL L P  118.277914\n",
       "1429              PUBLIC SERVICE CO HAYDEN PLT  106.690409\n",
       "1255       OWENS-BROCKWAY GLASS CONTAINER INC.   98.664760"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Do the same with PM2.5\n",
    "top_PM25 = df[[\"name\", \"PM25\"]].sort(\"PM25\", ascending=False).head(10)\n",
    "top_PM25"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great, now let's make bar charts for each. \n",
    "\n",
    "But before doing that, here's another way of making charts with pandas. \n",
    "\n",
    "Up to now we've been plotting using `matplotlib.pyplot`. But pandas has its own shorthand of making charts by calling  `plot` directly from the data frame or a series. You can then specify the kind of chart you want as an argument.\n",
    "\n",
    "In this case, we want a horizontal bar chart (`kind = 'barh'`).\n",
    "\n",
    "For reference, here are all the kinds of plots you can call ([more on this here](http://pandas.pydata.org/pandas-docs/stable/visualization.html)):\n",
    "* ‘bar’ or ‘barh’ for bar charts\n",
    "* ‘hist’ for histograms\n",
    "* ‘box’ for boxplots\n",
    "* ‘kde’ or 'density' for density plots\n",
    "* ‘area’ for area plots\n",
    "* ‘scatter’ for scatter plots\n",
    "* ‘hexbin’ for hexagonal bin plots\n",
    "* ‘pie’ for pie charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x108b63110>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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39LRws9ns9B/EykC53IcRMzmbw81tw4YNlJSUEBISwpEjR5g0aRItW7Zk+PDhtjnFxcUs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\nbQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108b47e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_VOC.plot(kind=\"barh\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What the? Where are the business names? This is happening because the pandas data frame we used has the row numbers as the index, or row labels. Let's fix this by making the names column the index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1094720d0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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O4cOHAwAsLS2hpqaGuLg41NfXv/tGtAIKCAghhBBCSLskeBLQtm3bcO3aNUyZMgUMw7Db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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109451590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_VOC = top_VOC.set_index(\"name\")\n",
    "top_VOC.plot(kind=\"barh\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10b295950>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YH/f9998TEhKCn58fy5Ytw83NjczMTLZt28bUqVO1LtA3bdpEgwYNtLa3srIy\neBxLWvfkyZNZsmQJ48aNY8mSJahUKrZv387w4cM5deoUkydPNrgPfd9/Ua5cucLevXvx8vIiOjpa\nOS6ffvopvr6+zJ49W0nybt26RUREBCNHjqRp06akp6drHYe8vDzOnDnDypUradu2LUuXLuWtt97S\n2t/PP/+sk/wWHjhnZmbGd999R2RkJLVr1y5xOwDc3d3ZsWMHDx8+5OTJkwwfPpwrV64QFxent/yI\nESMYPHgw8Ki/7htvvEFAQICShD8e2+NGJWcbFd+L757yr/ktrOSCRwghnpAkEuK5UqvVlClTBhsb\nGwB69OhBUlISO3fuNHpKNABLS0ulLgcHB/z8/Dh58qRR8RQeGDVt2jQuXbrE0aNHsbe3V5a7ubkR\nHBysVbaw3bt307VrVwYMGKAsq1WrFt26ddMqp1KplHgNxWNqaqqUsbe3p1u3bqxatQqA119/HVtb\nW2JjY/noo4+U7fLz81m3bh2hoaF6683NzSUiIoL27duzZs0aZXm1atVo3LgxOTk5WuWtra2LjNOY\num/dugVASkoKCxcuZObMmYSFhSnlRo4ciampKePGjaNr1654enoaPDbGWLNmDY0bN2b69OkEBgaS\nlZWFtbU1lpaWfPHFF/To0YPOnTvj6enJuHHjqFSpEh9++KHB41CtWjU6dOjAkCFDGDVqFO3atcPS\n0lIpa2Njo5NIFObm5oazszNTpkzhu+++M6otpUuXVuKws7MjLCyMGTNmcO/ePcqWLatTvly5cpQr\nV07528TEhHLlypX4OxVCCCH0kfdIiOfu8bvKpqam3L//ZF0pCl9cnj59miNHjuDl5fVEdRUUFLBx\n40aCg4O1kojCceq7aINHF3cpKSnKfM9Po3Cb0tLSSEhIwMPDA3h0QdinTx/WrFmjVW737t1kZmYa\nnIYuISGBzMxMRo0apXd94QtiYxVXd8WKFQGIi4ujQoUKyp3ywgYNGkS5cuXYsGFDkfsqaTKhVqtZ\nvXo1ISEhNGvWjBo1aihdxgDatGnDu+++S3h4OFu3bmXDhg0sXboUE5Pi77VERkZy69YtDh48aHRs\nkydPJj4+nsOHD5eoHYaYmppSUFBAfn7+U9UjhBBCGEMSCfHcFb7gSklJYf369Qa74xQnLCwMJycn\n7OzsaN68OT4+Plp3u41x8+ZNcnJycHd3N3rbqKgoKlWqhIeHB02aNCE0NJS1a9fy4MEDrXJ37tzB\nyclJ6/Oyn8wCAAAgAElEQVT49HEJCQk4OTlhb2+Ph4cHLi4uREdHK+v79+/P5cuXOXDggLJs9erV\ntGvXzuA80xcuXAAocds6d+6sE+ft27efqu7z58/j4uKi92Ld1NQUV1dXzp8/X2QdmmNT+NOlSxed\n5DQpKYnr168rLwoKCQkhJiZGq8zUqVNRq9W8++67jB8/nrp16xa5bw1NtyRN9yeN1157TSuux7uG\nAdSrV4/evXsX2YWrOGfPnmXlypV4eXlRvnz5J65HCCGEMJZ0bRLPneZi8MGDB+Tn59OlS5diB4Ya\nMm3aNNq3b8/Dhw85f/4848ePJywsjGXLlhldl7FdZwqrWrUq8fHxnDp1ikOHDnHkyBFGjRrFl19+\nyQ8//IC5uTnwaIxEUlKS1raa8REavr6+LFiwgNzcXFatWsWaNWu4du2a0m2mevXq+Pr6snr1avz8\n/Pj777/Zt28fK1eufGZtW7FihdYAacDgRasxdRdVtiT1aI5NYb/99hv9+vXTWhYTE8Nbb72FhYUF\n8GjQ9dSpU0lJSaFJkybAozELkZGRfPjhh1pjB560DTt27NAaR1KqlP77NuPGjcPLy4vt27fz2muv\nlWifZ86cwcnJiYcPH3Lv3j1atWqlcxyEEEKIf5okEuK501wMamZa0sywBFChQgUAcnJydPqb5+Tk\nKN1kNGxtbXF1dQWgRo0a3Llzh3fffZdx48Ypy0uqSpUqWFpacubMGeMb9f/VrVuXunXrMnjwYH76\n6Sc6derE5s2b6du3L/CoW1dxcZmZmSllZs+eze+//86HH37I5s2blTL9+/dn5MiRZGdns2bNGipV\nqkSXLl0M1lmjRg3g0QWpt7d3se1wcHAo8fGrWbNmiequWbMmP/30E/fv39dJnu7du6e8iKcohY+N\nRlZWltbf2dnZbNu2jfz8fGJjY5XlDx8+JDo6Wkkk4NHYA0MX/IZozo/H43BxcSlyjISGo6MjoaGh\nfPzxxwYHSz/Ozc2NDRs2KLM2FZ5tShgnLy+Pc+fSiy/4Ejh37tzzDuEf8Sq261Vok6Ojo3JzRrxY\ncnNz+fPPP/Wue9ZTD0siIZ47fReDGjVq1KBUqVKcOHFCq0xaWhq3bt0q9geh6eKSl5dndFylSpUi\nKCiItWvXMnbsWJ1uQnfv3kWlUhkcJ/E4TReY3Nxco2MpLCoqiq5du3L8+HFlrERgYCBjx45l3bp1\nrF69mt69e2slZI9r164dlStXZv78+XoH+mpefvMk/P39S1R3jx49WLp0KV9//TXh4eFaZVasWEFu\nbi7BwcFPFENh69evp0qVKjrjLY4cOcKECROYOXPmU/3HcNGiRVhaWj5xdzyAUaNGER0drQyiL46m\n65d4eubm5tRyfvnn9H9V303wKrbrVWyTeLFYWFj8z84xSSTEC61ChQqEhIQwceJETE1NqVevHn/+\n+SdTpkzB29ub5s2ba5XPzs7m6tWrFBQUcP78eebMmUOtWrW0ptcsKCjgl19+0eqSYmJiotN1Bx69\noj4pKYn27dszfvx4PD09KVu2LEeOHGHBggXExcXpnf71/fffx97enlatWuHg4MDVq1eZO3cu5cqV\n03r3glqt5tq1azrdY2xsbAzeGW/ZsiWNGjViwYIFfPvtt8Cji6Hg4GBmzpxJTk4O/fv3L/K4WlhY\nsHDhQt555x169epFeHg4bm5uZGVlsWPHDn755Ret6V8zMzO5evWqVh2WlpaYmZk9cd1eXl5ERkYy\nZcoU7t+/r4xt2LFjB5988gmjRo1SEqWnERMTw5tvvkmdOnW0llevXp2JEyeyadMmna5QhmiOw6O7\n2Of4+uuv2bdvH0uXLlWenmlcu3ZNZ9KASpUq6X16YGVlxfvvv8+MGTOMbJ1h6enppKamai1zc3Oj\nQoUKT9VtTwghhNCQREI8VyV5F8CsWbP4/PPPmTp1KpcuXcLGxgZ/f38mTZqkU1bzvgiVSkXVqlXx\n9fVl4sSJykW5SqUiLy+P1q1ba21XuXJl/vjjD514rKys2LNnDwsXLmTBggVaL6SLiIjAyclJb8x+\nfn6sXr2ab775hps3b2JtbU3jxo3ZvHkz1atXV2LJzc3VeYeASqXiP//5D66urgaPT2RkJGFhYaSl\npSl3pvv378/XX3+Nj49Pie5EdO7cmfj4eD7//HNCQ0PJycnBwcEBLy8v5X0KGkFBQTrbL1y40GDC\nUtK6p02bRoMGDVixYgWzZ88GoH79+ixatKjYF9IVde5olp84cYJff/2VefPm6ZQxNTWlU6dOrF69\nWiuRKOp81BwHc3NzHBwcaNGiBfv379d6IZ1mex8fH52YNm/eTJs2bfTuY+jQoSxbtszg4+iSxFfY\n478PlUrF2rVref311416/4YQQghhiCo7O1tuTQkhhDCo7bZrzzuEf8z8FlZ4VDEtvuAL7lXtLvMq\ntutVbBM86rb7Ko6ZeFXb9azI9K9CCCGEEOKpFPc09WX1qrbrWZGuTUIIIYo0v8WTDbx/EeXl5SnT\nLwPYWRielEAIIUTRJJEQQghRpFeh64/GuXPpr8QsTUII8SKQrk1CCCGEEEIIo0kiIYQQQgghhDCa\nJBJCCCGEEEIIo0kiIYQQQgghhDCaJBJCCCGEEEIIo0kiIYQQQgghhDCaJBJCCCGEEEIIo0kiIYQQ\nQgghhDCaJBJCCCGEEEIIo0kiIYQQQgghhDCayfMOQAjx6rh27Rrz5s0jPj6ev/76i8qVK1O/fn1C\nQ0Pp0KEDAA0bNuTy5cta21laWpKWlmaw3ps3bzJ69GgOHDhAQUEB9evXZ+7cudSvX7/YmKytrVm1\nahWBgYF61z98+JBFixaxZs0aLl++jKmpKW5ubvTu3ZuhQ4fqjbewli1bsn37doPlRo0axaRJk0hP\nT6dx48Z669i4cSP+/v7ExsYSFRVV5P4K09S5f/9+g3U/rnCc5ubmuLq6MnToUAYMGGBwm+M37peo\n7pdBnpkt/y1Be+wsSmNvUfp/EJEQQry8JJEQQjwT6enpBAQEULFiRaZMmUKDBg0oKCjgwIEDjBo1\nil9//RUAlUpFVFQUgwYNUrYtVaroh6OTJk3i2LFjrFu3jqpVq/LLL7+gUqmeSdyzZs1i5cqVzJ07\nF09PT3Jzczl58qRysX3w4EEePnwIwC+//EJQUBD79+/H0dERgDJlyhhsF4CFhYXW35s2baJBgwZa\ny6ysrJ5JW0qicJz//e9/iY2N5b333sPS0pI333xT7zajkrP/Z/H9b9wrtsT8FlaSSAghRDEkkRBC\nPBMffPABpUqVYv/+/VoXz7Vq1aJXr15aZcuXL4+NjU2J6y5dujRNmzalWbNmALi6uj6TmAF2797N\nu+++S/fu3ZVldevWVf5dqVIl5d/W1tYAVK5cWW/8JWmXtbW1UW3/J2jitLGxYcKECWzZsoWdO3ca\nTCSEEEIIfWSMhBDiqWVlZZGQkMDgwYN17sADVKxYUetvtVptVP2dOnVix44dxMfHP1Wc+tjZ2ZGU\nlMT169efui5j2/WiMDU15f79V6f7khBCiP8NSSSEEE/twoULqNVq3N3diy2rVquZPn06Tk5Oymf+\n/PkGy58+fZphw4axdu1aZsyYwcaNG5V1Fy9exNramgsXLjxx7DNmzCArK4vatWvTvHlzRowYwfbt\n242uR1+7nJycdJKfzp0765S5ffv2E8f/JDQJz4MHD4iNjeXUqVO0bdv2fxqDEEKIl590bRJCPDVj\n7sSrVCoiIyPp37+/sqyoMQKzZs2iU6dOtGvXjnr16hEQEMD169cJCwvjt99+w97enurVqz9x7LVr\n1+bw4cOcOHGCw4cPk5yczMCBA/H392fdunUlHouhr10Atra2Wn+vWLGCevXqaS0rX778E8dvLE3C\nM3v2bO7du4epqSkjR47knXfe+Z/FIIQQ4tUgiYQQ4qnVqFEDlUrFmTNn6NKlS7Hlra2tSzzO4fff\nfyc4OBgAe3t7NmzYoCQTJ0+epG/fvk8TOvAoCfDw8MDDw4Nhw4YRFxfH0KFDOXToEC1btixxPSVp\nl4ODwzMd42GswgmPubk5VatWfW6xvMjy8vI4dy79eYdhlHPnzj3vEP4Rr2K7XsU2gbTrZVCrVq1n\nWp8kEkKIp2ZtbU27du1Yvnw5Q4cOpVy5clrrs7Ozn3hmInt7exITExkzZgzw6P8E4+Li6Nq1KyYm\nJqxcufKp43+cpotWbm7uM6/7RWBMIvdvZW5uTi3nZ/sf3H/SuXPnnvkFwovgVWzXq9gmkHb9W0ki\nIYR4Jj799FMCAgLw8/Nj/Pjx1KtXD7VaTWJiIvPnz1emfzXWyJEjCQ4O5r333mPw4MGo1Wr27NlD\nqVKluHfvHps3by7yHQjFCQkJwcfHB29vb2xtbUlPT+fjjz+matWqeHt7l7getVrN7du3uXr1qtZy\nc3NzrcHmmZmZOmUsLS0xMzMDoKCggF9++UWru5iJiYlOd6jC/vjjD50pdGvXrk3ZsmVLHL8QQghh\nLEkkhBDPhKurKwcPHmTevHlMnjyZv//+m0qVKlGvXj1mzpz5xPX6+/uzfft2PvnkE7p06YJKpaJV\nq1b88MMPHD58mA8++ABnZ2f8/f2fqP727duzadMmPv/8c3JycrCxscHHx4fFixfrfYpiaMyESqVi\nzpw5zJkzR2t5z549Wbp0qfJ3UFCQzrYLFy6kf//+qFQq8vLyaN26tdb6ypUr88cffxhsw5AhQ3Ri\nSU5Opk6dOga3EUIIIZ6WKjs7++Wcr1AIIcT/RNtt1553CP9z81tY4VHF9HmHUWKvaveLV7Fdr2Kb\nQNr1byVPJIQQQhRpfov/3Zu3/2l5eXmYm5sXW85O3mothBDFkkRCCCFEkV6mO/PFOXcu/aUaRC2E\nEC8yeSGdEEIIIYQQwmiSSAghhBBCCCGMJomEEEIIIYQQwmiSSAghhBBCCCGMJomEEEIIIYQQwmiS\nSAghhBBCCCGMJomEEEIIIYQQwmiSSAghhBBCCCGMJomEEEIIIYQQwmiSSAghhBBCCCGMZvK8AxBC\nCPFiO37j/vMO4ZnJM7Plv8+xPXYWpbG3KP3c9i+EEM+SJBLipWZtbV3k+r59+/LFF19olbOwsMDZ\n2Zn+/fsTERGhLE9MTCQwMJALFy4YrPfGjRvMnDmTPXv2cPXqVSwtLalbty6jRo3Czc2Nxo0bFxnP\nhx9+SFRUFAC+vr78/vvvHDt2jBo1apCenl6i7fv06UOjRo30rt+4cSP+/v4Gt09NTWXBggUkJyeT\nmZmJjY0N9erVIyQkhC5duqBSqYqMQ1N/bGwskZGRtGnThi1btmiVsba2ZtWqVQQGBgLQsGFDLl++\nrFPXqFGjmDRpks7+KlSogJubG8OGDaNXr146240dO5bly5ezYMECQkJCityHRsuWLdm+fTsNGzYk\nNDSU4cOHK+vOnj3L7NmzSUxMJCcnBzs7O7p27coHH3yAlZWVUq5Lly4kJyezZMkSrbhiY2OJiooq\ncv8AFy9eZN68eRw4cIDr169ja2uLp6cnEREReHt7K8dOw9B5qrF48WImTpzI6NGjmTBhgtY6Q+fy\njh07WL58Oampqdy9exdHR0eaNm1KaGgoHh4eBmMflZxdZNtePvee257nt7CSREII8cqQREK81M6e\nPav8e/fu3YwcOVJrmZmZmfLvhQsXEhAQwJ07d9i0aRMTJkzAxsaGnj17lnh//fv35969eyxevJjq\n1atz/fp1kpKSyMrKonXr1lr7XrFiBbGxsezfv19ZZmFhAUBKSgrnzp3jtddeIyYmhilTpuDs7Fzs\n9uXKleP69esAbNq0iQYNGmjFV/jC93Hff/89ISEh+Pn58eWXX1K9enXy8/M5cuQI8+bNo0mTJtjb\n2yvli6u/dOnSJCcns2/fviKTF5VKRVRUFIMGDdJarjkWj+8vOzubFStWEBYWRrVq1WjevLlS5t69\ne6xfvx4vLy+io6OVROLgwYM8fPgQgF9++YWgoCD279+Po6MjAGXKlFFiUalUSn0pKSl069aNli1b\nsmbNGuzt7fn111+ZPHkye/bsIT4+HktLS2VbMzMzZsyYQffu3TE1NTXY5scdP36cbt26UadOHT77\n7DPc3d25c+cO8fHxjB07lgMHDihlS3qerl69Gi8vL9asWcO4ceMoVaronqrTpk1jwYIFDB06lA8/\n/BBnZ2cyMzPZv38/EydOZMeOHSVujxBCCAGSSIiXnI2NjfJvzQVf4WWFWVpaYmNjg42NDe+//z6L\nFy/m2LFjJU4ksrOz+emnn9iyZQutW7cGwMnJSetObuF9ly9fnlKlSumNJyYmhjfeeINOnToxceJE\nJk6cSOnSpUu8PTy6e21o3ePu3LlDREQEAQEBREdHa62rWbMmffv2Nbp+MzMz+vTpw+TJk/Hz89O6\nQH9c+fLli41Vsz8bGxsmTJjAsmXLSElJ0Uoktm/fjrm5OcuXL6dJkyacOnWKunXrUqlSJa16ACpX\nrlzkPtVqNZGRkdSqVYu1a9cqyx0dHWnUqBGenp5Mnz6dTz/9VFnXvXt39u7dy/Lly/U+JTC0n2HD\nhuHm5sYPP/ygdZzq16+vk2CV5Dw9cuQIaWlp/Oc//6F58+bs2bOHjh07Gozh2LFjfPbZZ8yePZvQ\n0FBluZOTE6+99hojR44sUVuEEEKIwmSwtfjXUKvVADx8+JDNmzeTlZVVZHeOx5UvX57y5cuza9cu\n7t178q4RmjvNAwYMoFu3bty/f5/vv//+iesriX379pGZmfnMLxjHjh1LWloacXFxRZbTHPuSyM/P\nZ9WqVahUKp3vJzo6mr59++Lq6kr79u11kiJjpKamcvr0aSIjI3XW2dnZERwczIYNG7SWlytXjqio\nKObNm0dOTo5R+xkxYoTeZKtixYpaf5fkPI2OjiYwMBAHBwd69uxZ7HFYv349FSpUYPDgwSWKWQgh\nhCgJSSTEv0ZYWBhOTk5UrVqVIUOGMGfOHPr06VPi7U1MTPjiiy+Ii4vDxcWF119/nYkTJ5KSkmJU\nHFu2bKFy5cq0adMGU1NTevfu/UQXxJ07d8bJyUnrc/v2bb1lz58/Dzx6+qDx22+/4ejoqGy7fv16\no+u3sbEhMjKSGTNmkJ+fr3ffarWa6dOn69QVHx+vd392dnbMnDmTb775Bl9fX2V9WloaycnJ9O/f\nH4ABAwYQFxfH/ftPNnBWc0zc3d31rnd3dyc7O5ubN28qy1QqFe+88w6VKlXi888/L9F+Lly4UOR+\nHlfcefrf//6XrVu3MmDAAODRcYiPj+fatWsG6zx//jwuLi5a3Z9WrFih9X38+eefJYpPCCGE0JCu\nTeJfY9q0abRv355Lly7x0UcfsXPnToYMGWJUHYGBgXTs2JHDhw9z5MgREhISlEGv77//fonqiImJ\noV+/fsrfAwYMwNfXlytXrmBnZ1fiWFasWEG9evW0lpUvX77E27u7u3Po0CHUajUtW7bkwYMHT1R/\nREQEK1euZNmyZXq7+6hUKiIjI5UEQMPW1lZnf3Xr1uXcuXOMHj2aPXv20K1bN2X96tWradWqFS4u\nLgB07NiRsmXLsnPnTrp3717idj+t0qVLM3HiRMLDw7W6CRlizNMYKP483bRpE1WrVlWSrAYNGtCo\nUSO+++67Ip84PR5Hz549ad++Pb/99hv9+vWjoKDAqDjFk8nLy+PcufR/pO5z5879I/U+b69iu17F\nNoG062VQq1atZ1qfJBLiX8PW1hZXV1dcXV2JiYnB29ub9evXExwcbFQ9ZcuWpW3btrRt25axY8cy\nYsQIZs2axYgRIzAxKfondfbsWX7++WeOHj3KzJkzleUFBQXExsYyevToEsfh4OCAq6tricpqnkSc\nPXuWpk2bAo8GIGu219flpqT1ly9fnrFjxzJjxgytBKkwa2vrYutycHDAzc0NNzc3lixZwhtvvEG/\nfv3w8fHh4cOHrFmzhitXrlClShVlm4KCAqKjo58okahRowYAp0+fpmHDhjrrz5w5g7W1NZUrV9ZZ\n161bNxYtWsQnn3yiNYajqP2cOXNG734eV9x5Gh0dzYULF3SOQ3Z2tsFEombNmvz00088ePBAOUcr\nVqxIxYoVycrKKjYm8eyYm5tTy/nZ/occHl3oPOsLhBfBq9iuV7FNIO36t5KuTeJfyc3NjeDgYObP\nn//Udbm7u/PgwQPu3r1bbNmYmBiaNm3KoUOHSEpKUj5RUVGsXr36qWMxxN/fn0qVKvHZZ5/9I/Vr\nuvs8i+MJj6bG9fX1Verbu3cvWVlZHDhwQOu4rVu3joMHD5KRkWH0Pho1akTt2rVZvHixzt36v//+\nm/Xr1xMUFGRw+6lTp/Ldd99x+vTpYvdTp04dFi5cqPeuf3a24alVHz9PT506RUpKCps3b9Y6DgkJ\nCWRkZJCcnKy3nh49enDnzh2WLl1aZKxCCCGEMeSJhPjXioiIoGXLlsTHx/P6668XWz4zM5MBAwbQ\nv39/6tWrR/ny5Tlx4gQLFy6kbdu2xXYrys/PZ+3atYwZM4Y6deporbOysmLOnDn8+OOPyoxQJYnn\n6tWrWsssLS21przVsLCwYNGiRbzzzjv06NGD8PBwqlevTm5uLvv37+fu3buULq09t70x9Wu6+wwd\nOlRnnVqt5vbt2zp1mZub6ww0LiwyMpK+ffty6tQpoqOj6dChA6+99ppWmTp16lCrVi1Wr17NuHHj\nDNZlyOLFi3nzzTfp06cPo0ePxt7ent9++41Jkybh4uKi9X4GtVqtlXD4+vrSrl07li1bVuyTqC++\n+II333yTgIAARo8ejbu7O7m5uezdu5ctW7ZoTfH7uMLn6f79+2nUqBFt2rTRKdemTRuio6Np0aKF\nzjovLy9GjhzJpEmTuHTpEoGBgTg5OXH9+nW+/fZbVCqVzvcvhBBCFEeeSIhXSlFTkD6ufv36+Pn5\nsXDhwhJtX758eby9vZVuNy1atGDatGn07NmTlStXFhvP7t27yczMVF7UVpidnR3NmjXTeSpRVDxB\nQUHUqVNH6/P4gOnCOnfuzJ49e6hYsaLyErSuXbuyb98+vvzyS50uXsXV/3hs3bp1o2HDhjrLVSoV\nc+bM0alrzJgxRbYzICCAmjVrMmnSJJ3xEo/vd82aNTr7LAkvLy8SEhIoV64cffv2xdPTkzFjxtCh\nQwd++OEHZUphTZ2P1ztlyhTy8/OL3Z+npycHDhygVq1avP/++zRr1ozevXtz5MgRpk2bVuS2mvN0\n7ty5bNiwocjjsH37dmVAvL5Yv/nmG37//Xf69u1LkyZNCAkJIS8vj127duHg4FBkHEIIIcTjVNnZ\n2caNBBRCCPGv0nab4RmhhHHmt7DCo0rJX2ZYUq9qP+5XsV2vYptA2vVvJV2bhBBCFGl+C8NvTH/Z\n5OXlYW5u/tz2b2chXciEEK8OSSSEEEIU6Z+4g/68nDuX/o/MmiSEEP9GMkZCCCGEEEIIYTRJJIQQ\nQgghhBBGk0RCCCGEEEIIYTRJJIQQQgghhBBGk0RCCCGEEEIIYTRJJIQQQgghhBBGk0RCCCGEEEII\nYTSj3yORk5NDSkoKN27coE2bNlStWvWfiEsIIYQQQgjxAjPqicTcuXOpW7cuQUFBhIWFcfr0aQBu\n3LiBnZ0dX3/99T8SpBBCCCGEEOLFUuJEYuXKlcyYMYPg4GC++eYb1Gq1sq5KlSp06dKFrVu3/iNB\nCiGEEEIIIV4sJe7atHTpUrp168aCBQu4efOmzvqGDRvy1VdfPdPghBBCPH/Hb9x/3iE8M3lmtvz3\nBW2PnUVp7C1KP+8whBCixEqcSKSlpREeHm5wvZWVFVlZWc8kKPHiCw8PZ+3atQCYmJjg6OhI165d\n+eijj7CwsCAxMZHAwEAuXLiAtbW11rYNGzYkNDSU4cOHA2itNzExwd7enqCgICZMmEDp0o/+oxob\nG0tUVBSXL182GE9mZibr1q1Tlt2+fZsFCxawfft2MjIyqFChAu7u7gwcOJC33noLlUqlt67o6GiW\nL1/OxYsXKVWqFM7OznTq1IkJEyYosURGRupsp1KpuHLlCqamplrHp3Tp0tja2tK6dWumTJmCnZ0d\nvXv3Ji8vT+9TvDNnzuDj48PmzZtp27Yt1tbWrFq1isDAQKVMamoq8+fPJzk5mezsbBwdHfHx8SEy\nMpJ69eqRnp5O48aN9bZv48aN+Pv7611Xkro11q9fz7Jlyzh16hRqtZq6desSGhpKz549Ddatce3a\nNebNm0d8fDx//fUXlStXpn79+oSGhtKhQwdA9zzRWLRoEcuXLyc1NRV4Nt9HYceOHWPu3Ln8/PPP\n5Obm4uLiQlBQEO+99x5ly5ZVyumLb8aMGXzxxRd88803dOzYkS5dupCcnKwTW1BQECtWrADQ+X1o\nzJ8/n3feeUfvusL1mpqa4uzsTN++fXnvvfcoVaqU3t+foVg0qlWrxsmTJ/WuG5WcbXC7l9O95x2A\nXvNbWEkiIYR4qZQ4kbC0tOT69esG158+fVoGXv+LqFQq/Pz8WLp0Kfn5+SQnJzNixAjy8vKYO3du\nsds+fhG/cOFCAgICyM/P5/jx44SHh2NlZcXIkSNLHE/hOrOzs+nUqRO3bt1i/PjxNGnSBFNTU5KT\nk/n000/x9vbG2dlZp56YmBg+/PBDZs6cSZs2bcjPz+f333/n6NGjWuUsLCw4ceKEzvampqY6x+fB\ngwecPn2a4cOHExYWxpYtWwgJCaFfv35kZGRQrVo1nRiqVatG27Zt9bb1+++/JyQkBD8/P5YtW4ab\nmxuZmZls27aNqVOnaiVTmzZtokGDBlrbW1lZGTyOJa178uTJLFmyhHHjxrFkyRJUKhXbt29n+PDh\nnDp1ismTJxvcR3p6OgEBAVSsWJEpU6bQoEEDCgoKOHDgAKNGjeLXX39VjqGhZO9xT/t9aOzatYsB\nAwbQq1cvtm7dSqVKlfj555+ZOHEiBw8eZOvWrZQpU0YnvoKCAsaMGcPGjRvZtGkTPj4+Spl+/fox\naZY3tisAACAASURBVNIkrbgKJyTwf+d/YRUqVDDY3sL13r17l++//56oqChMTEwYMWKE3m1iY2PJ\nz88HIDMzEx8fH2JiYmjWrBmAkrQLIYQQJVXiRKJjx46sWrWKQYMG6az79ddfiY6Opn///s80OPHi\nUqvVlClTBhsbGwB69OhBUlISO3fuLDaR0MfS0lKpy8HBAT8/P4N3Rw3FU3jczrRp07h06RJHjx7F\n3t5eWe7m5kZwcLBW2cJ2795N165dGTBggLKsVq1adOvWTaucSqVS4jUUj6mpqVLG3t6ebt26sWrV\nKgBef/11bG1tiY2N5aOPPlK2y8/PZ926dYSGhuqtNzc3l4iICNq3b8+aNWuU5dWqVaNx48bk5ORo\nlbe2ti4yTmPqvnXrFgApKSksXLiQmTNnEhYWppQbOXIkpqamjBs3jq5du+Lp6al3Px988AGlSpVi\n//79WFhYKMtr1apFr169ShTr4572+9C0f/jw4XTs2JHFixcry52cnKhZsyZ+fn4sWbJE5wnJ/fv3\nCQsL4/Dhw+zcuZP69etrrTc3Ny/2Oyh8/pdU4XqHDBnC7t272blzp8FEonACWarUo+FxxpwfQggh\nxONKPNh6/PjxALRo0YKpU6cCj+5wDRw4EH9/f2xtbRk7duw/E6V4IT1+t9jU1JT795+s73HhC/vT\np09z5MgRvLy8nqiugoICNm7cSHBwsFYSUTjOx+8Ia9jZ2ZGSkkJaWtoT7buwwm1KS0sjISEBDw8P\n4FEXrj59+rBmzRqtcrt37yYzM5O3335bb50JCQlkZmYyatQovestLS2fON7i6q5YsSIAcXFxVKhQ\ngcGDB+uUGTRoEOXKlWPDhg1668jKyiIhIYHBgwdrJRGP70PDUML3JIr6PuD/2q/vKVijRo1o06YN\n69ev11p+584devfuzYkTJ9i9e7dOElHSNjyLdj7N708IIYR4EiVOJOzs7Ni/fz8dO3Zk27ZtwKM+\n0gkJCfTs2ZO9e/dSuXLlfyxQ8eIpfPGTkpLC+vXrDXbHKU5YWBhOTk7Y2dnRvHlzfHx8tO52G+Pm\nzZvk5OTg7u5u9LZRUVFUqlQJDw8PmjRpQmhoKGvXruXBgwda5e7cuYOTk5PW5/GuKQkJCTg5OWFv\nb4+HhwcuLi5ER0cr6/v378/ly5c5cOCAsmz16tW0a9cOBwcHvfFduHABoMRt69y5s06ct2/ffqq6\nz58/j4uLCyYmug80TU1NcXV15fz58wb3oVarSxS/Wq1m+vTpOvFPnz5dJ4l9Ft+HJmZDsbm7u/PH\nH39oxffZZ5+RkpLC7t27cXV11duGVatW6cS2cuVKrXKa87/w59SpU8UeH3iUOO/du5f9+/c/8e9P\nCCHE/2PvzuN6yv4/gL9u0Sal9CltKhXJMnaFUtkiykiEFIYWwjQhY18nZIYSgyzTikRSYhhCWSJL\nmhmqKZVllBBGpfX3h9/nfrt9Pp/6fJIxeD8fjx4PnXvOuefcRefce865pCkk+iAdj8dDYGAgtm7d\niuLiYtTU1EBNTY3G1n6h+A2zqqoqVFZWws7ODps2bWpSXmvXrsXQoUNRXV2NnJwcLF26FJ6enti9\ne7fEeb3P010NDQ2cPn0ad+/exaVLl3Dt2jX4+Phgx44d+PXXXyEvLw/g3Zj8lJQUTlr+eHy+gQMH\nIjAwEKWlpQgNDUVUVBSKiorYya8dOnTAwIEDERERAWtra/z99984d+6cQCPzfeq2Z88ezgRpAFBU\nVHzvvBuK29Rt9TEMA29vb4Ehk2FhYQJvPJrjfEiKP+/i4sWL2LBhA7Zs2SI0zrhx47B48WJOuKqq\nKud3/vVfl7a2tsh98zsoBw4cYN9CODs7w8/Pr0l1If8NZWVlyM7Ob3L67OzsZizNf8fnWK/PsU4A\n1etTYGxs3Kz5Sfxla6Dx8cjky8BvmPFXWqrboeRPFH358qVAQ+3ly5cCQ1jU1dXZJ7qGhoZ48+YN\nZsyYgSVLlgh90tsQNTU1KCsrIzMzU/JK/b/OnTujc+fOmDlzJq5evYqRI0ciNjYWkydPBvDuHmis\nXHJycmycjRs34s8//8TixYsRGxvLxpk6dSrmz5+PkpISREVFQVVVFXZ2diLzNDQ0BPBuZad+/fo1\nWg8tLS2xj5+RkZFYeRsZGeHq1auoqKgQaKy/ffsWeXl5GDx4sMjyMwyDzMzMBuvJp6KiIlB+YQ3/\n5jgf/Prfu3ePnYBcV2ZmJhuHb9CgQZgzZw4mTZqE6upqBAUFCaRTUlJqtGx1r39x1O2gyMjIQFNT\nU+yJ6eS/S15eHsa6Tfsjn52d3ewNhP+Cz7Fen2OdAKrXl0qiL1u/evUKYWFhWLduHRYsWABfX1+B\nH/Ll4DfMdHR0BN5KGRoaQkpKSmAlnby8PLx69arRm5LfKCorK5O4XFJSUnB0dMThw4fx+PFjge3l\n5eV4+1b85R87deoE4N1k3Pfh5+eH8+fP49atW2yYvb09ZGVlcejQIURERMDZ2bnBN3xDhgxB27Zt\nhT79Bt6tVtVUNjY2YuU9fvx4vHnzRuiX7Pfs2YPS0lI4OTkJzUNFRQVDhgxBSEgI3rx506zll1T9\n82FjYwNVVVWhnYHbt2/j4sWLQutlYWGBw4cPIzY2FnPmzGnWeR0N4XdQtLS0qBNBCCHkoxD7jcS5\nc+cwbdo0keOr+X788cf3LhT59LVu3Rqurq5Yvnw5ZGRkYGpqikePHmHVqlXo168fzM3NOfFLSkpQ\nWFiImpoa5OTkYNOmTTA2NmYb8cC7seAZGRmchlqLFi0Ehu4AwPLly5GSkoKhQ4di6dKl6NWrF2Rl\nZXHt2jUEBgYiOjpa6PKv3333HTQ1NWFhYQEtLS0UFhZi8+bNaNWqFefbC7W1tSgqKhJoNPJ4PHZF\nnPoGDRqEr776CoGBgfjll18AvHsC6eTkBH9/f7x8+bLRlc8UFBQQFBSEadOmYeLEifDy8oKBgQFe\nvHiBhIQEZGRkcJZ/ff78OQoLCzl5KCsrQ05Orsl59+nTB97e3li1ahUqKipgZ2cHhmGQkJCAH374\nAT4+PpxJzPUFBATA1tYW1tbWWLp0KUxNTVFbW4vk5GRs2bKFXf5VEs1xPhQUFBAYGIjp06fD29sb\n7u7uUFFRwbVr17B8+XKYm5uL/JaOubk5jhw5gvHjx6O6uho7duyAlJQUamtrUVpaKnAOZGRkOG9W\n+Nd/XYqKimjVqpXI+orTYfnjjz8E3v5169at0XSEEEKIOMTuSPj5+UFJSQmhoaHo1avXe60OQz59\n4qzxv2HDBmzduhWrV6/GgwcPwOPxYGNjI7CmPgB2pRyGYaChoYGBAwdi+fLlbCOQYRiUlZXB0tKS\nk65t27b466+/BMrTpk0bnDlzBkFBQQgMDOR8kG7OnDnQ0dERWmZra2tERERg//79ePbsGVRUVNCj\nRw/ExsaiQ4cObFlKS0s5nRx++M2bN6Gvry/y+Hh7e8PT0xN5eXnsUJapU6di7969MDMzE+v16ahR\no3D69Gls3boV7u7uePnyJbS0tNCnTx/2o3l8jo6OAumDgoJEdljEzXvt2rXo2rUr9uzZg40bNwIA\nunTpgm3btjX6QTp9fX1cuHABP/74I1auXIm///4bqqqqMDU1hb+/f6P1B7grhjXn+Rg9ejQSExOx\nefNm2Nvbo6ysDHp6enBzc4OPj4/QCeZ8/fr1w7FjxzBu3Dh4enqy39eIjIxEZGQkJ66ZmRlOnjzJ\n/i5spagFCxawq+UJq39D9x9/25gxYwTC+R91pLcYhBBC3hdTUlIi1nt4TU1NrFy5sskr6RBCCPk0\nWR0v+thF+CJsGdAGPdVkGo8oxOc6jvtzrNfnWCeA6vWlEvuNhKmpqcDHrgghhHz+tgwQ/TX0T01Z\nWRm7+tp/TTsFWgGREPJpEbsjsXr1akyfPh3W1tZirRZDCCHk89DUp+T/RdnZ+U1eGYkQQgiX2B2J\nQYMGYe3atbC1tYWxsTG0tbWFri5T/8uvhBBCCCGEkM+P2B2Jo0ePwtvbG7W1tXjy5InQpTBp8h4h\nhBBCCCFfBrE7EmvWrEHHjh0RFhYm8FEmQgghhBBCyJdF7A/SFRUVYcaMGdSJIIQQQgghhIjfkejR\nowcKCgo+ZFkIIYQQQgghnwixOxIBAQE4evQooqOjP2R5CCGEEEIIIZ8AsedITJ8+HVVVVfDw8ICP\njw80NTU5qzbV1taCYRikpqZ+kIISQgghhBBC/jvE7kjweDyoq6vD0NBQZBxatYkQQgghhJAvg9gd\niRMnTnzIchBCCCGEEEI+IWLPkSCEEEIIIYQQPrHfSPBVVFQgOzsbr169Qk1NjcD2gQMHNkvBCCGE\n/DfcKq742EVoNmVy6vjnP1qfdgrS0FSQbjwiIYT8R4jdkaitrcWaNWsQEhKCN2/eCI3DMAyeP3/e\nbIX7mLy8vHDw4EEAQIsWLaCtrY0xY8bg+++/h4KCAvLz89GjRw8kJSWhR48eDea1aNEihISEIDAw\nEK6urgCAbt264eHDhyLTDBw4EJcuXRK5nWEY3L59G5GRkdi0aZPAdg0NDdy7d09o2uTkZNjb27O/\nKysrw8TEBAsWLMDQoUPZcH9/f8THx+Py5csIDg7Gpk2bkJmZCXl5eU5+1dXV6Nq1K6ZMmYJly5bB\nzs4Oly9fFtivo6Mj9uzZAwBQUVFhwxUUFKCrq4upU6dizpw5IusMgJO3jIwMdHV1MXnyZHz77beQ\nknr3gq2mpgYhISEIDw9HTk4OWrZsiR49emDevHls/f755x/o6+tjx44dmDBhApv/3LlzERERIXBe\nbW1toaenh127diEyMhLe3t4CZWMYBk+ePIGMjAzn+pGWloa6ujosLS2xatUqtGvXrsE6Au867J07\nd0ZZWRnu3bsHJSUlzvZu3brB3d0dc+fO5YTXPWd1j7EwkydPxvbt26GiooLQ0FDONQEACxcuxN27\nd5GQkMCGlZSUYPPmzUhISMDjx4+hrKwMS0tLLF68GMbGxpxy8K9LhmHA4/HQt29frFy5khPPzs4O\npqamCAgIaLS8Q4YMwe3btzF37lzMnz+fs83d3R1//vknzp8/jxYtJH4+AgASnbOioiJ06dIFGhoa\nyMjIYOeH7d+/H8uWLUN+fj5bjoqKCujp6cHAwIBzX+Tm5qJ3796Ii4uDpaUl51jUFRcXh2nTpuHF\nixcA/nf/5ubmQkVFhf2/iK9Vq1bQ1NSEubk5PDw80KVLF3Zb/Xu/ruvXr4v8TpDP5RKxjuGn4+3H\nLoBQWwa0oY4EIeSTIvZf3K1bt2Lr1q1wc3PDgAED4OHhgdWrV0NZWRm7d++GtLQ01qxZ8yHL+q9i\nGAbW1tbYtWsXKisrcfnyZcybNw9lZWXYvHmz2Pm8ffsWhw8fRp8+fRAWFsZ2JC5cuIDq6moAQEZG\nBhwdHZGUlARtbW0A7xofMjIyAN514kaPHg1bW1tOw7Ft27YAgI4dO3IaewA4K2qJkpqaChUVFTx9\n+hSbN2/GlClTkJqaCn19fYG4kyZNwtq1a3Hs2DFMmjSJs+3MmTMoLCyEi4sLgHfHzsXFBStWrODE\nk5WV5fweFBQEW1tbvHnzBkePHsWyZcvA4/E4Dfv66uZdXl6OU6dOwc/PDy1atMC8efMAADNnzsTZ\ns2exatUq2NjYoLy8HAcOHMDEiRMREBCAGTNmQFFREb1790ZKSgpnf8nJydDR0UFycjLbOHvz5g1u\n3rzJnjvgXefn9u3bAuXjn7O6109VVRXu3buHuXPnwtPTE8eOHRNZP74TJ05ASkoK6urqiImJwYwZ\nMwSOQ2OLG2RlZbH/PnnyJObPn88Jk5OTa7QcdfdRUlKC4cOHQ0pKChs3bkTXrl3x999/Y/PmzbCx\nscHx48fRs2dPNj7/uqypqUFubi4WLFiAiRMn4ubNm0LrIU55k5KS4O7ujuHDh6Nz584AgISEBBw/\nfhxJSUlN7kTwyyLuOTtw4ACMjIzw6NEjnD17lu2gWlpaorS0FGlpaTAzMwMApKWlQVlZGbm5uXj2\n7Bl73yYnJ0NOTo6NJ845bcjRo0fRtWtXlJWVITMzE/v27YOVlRV27dqFcePGceLy7/26+OUihBBC\nxCX2HImIiAiMGTMGW7duxZAhQwAAX331Fdzc3HDu3DlUV1cjJSXlgxX031ZbW4uWLVuCx+NBS0sL\n48ePx4QJEySedB4fHw95eXmEhITg1q1buHv3LgBAVVUVPB4PPB6P/YPetm1bNkxbW5v9t7q6Olq0\naIFWrVqxYTwej30CLy0tzQnn8XhQVVVttGz8uKampvD19UVFRQXu3LkjNG7btm0xcuRIRERECGwL\nDw+HhYUFpwMiLy8vUKb6T9WVlZXB4/Ggr6+P7777DioqKkhLS2u03Py8dXV1MWvWLFhZWbHnJTY2\nFrGxsfj5558xffp06OnpoVOnTli1ahXc3d3x/fff4/HjxwAACwsLJCcns/k+ePAAf//9N7y9vTnX\ncmpqKiorK2FpacmG8Z+y1//hq62thYyMDHg8HjQ1NWFtbQ0HBwex6sc/plOmTMHUqVMRHh4uVpr6\n6pZLWVlZIKx169aN5lFbW8v+e+3atXj8+DHi4uIwYsQIaGtro0+fPjhw4AA6dOgg8DaJf11qaGjA\n3Nwcrq6uuH//PvtkvSnltbe3h4ODA7y8vFBVVYVnz57Bx8cHS5cuZTsWTSXJOYuIiMCsWbPw9ddf\nc86PoaEhNDU1OddVcnIyLC0t0aNHD851lZycjL59+7Kdz/eloqICHo+H9u3bY9iwYThw4ADGjh0L\nHx8fvHz5khNX2LXL//+EEEIIEZfYfzkePnwIKysrAP972v327bvXw7KysnB2dmaHBXwu6j8dlJGR\nQUWFZGNrw8LCMHnyZOjr62Po0KEICwtrziK+F34jsbS0FJGRkWjZsiW6d+8uMv7UqVNx5coV3L9/\nnw0rKirC6dOnMXXqVKF5i7P/6upqxMbG4sWLF5wn2uKqe16io6NhZGSEUaNGCcSbN28eKioqcPz4\ncQDAoEGDkJeXh0ePHgF417Dr1asXhg0bhitXrrBzgJKTk6Gvrw8dHR2JylX3GOTl5eHs2bNi1a+g\noAAXL16Eq6srpkyZgt9//x2///67RPuWVGPnq6amBkeOHIGTkxM0NDQ42xiGgbe3N+7evYs//vhD\naPrCwkLEx8fDwMCg0SFMjQkICEBxcTECAgLg6+sLY2NjgSFeTSXOObt8+TIeP34MJycnuLm54eTJ\nk3j27Bm7fdCgQZyOREpKCiwsLESGi9p/c/D29sarV69w4cKFD7ofQgghXyaxOxJt2rRBeXk5AKB1\n69aQkZHhjPGXlZXl/DH9HNT9Y3vjxg0cPnyY7UyJIy8vD5cvX2Yb2W5uboiOjpa4M9KYzMxM6Ojo\ncH5mzZrVaLru3buz8WNiYhAbGyt0WBOfjY0NtLW1OW8lDh48CEVFRc6469raWoSGhgqUad++fZz8\nPD09oaOjAw0NDcyaNQubNm0SGDYlDP+81NTU4LfffkNSUhJ7XnJyctCxY0eh6TQ1NdG6dWvk5OQA\nAPr37w8ZGRm2cZecnIxBgwahQ4cOUFRUZIcu8Z8o1/XmzRuB+tna2nLinD17Fjo6OtDU1ETPnj2h\np6cnVkcyMjIS5ubm6NChA9q1a4cRI0YgNDS00XTvg38u6v6Ehoayneni4mK8fPlS5LHlh//1119s\nGP+61NLSgomJCcrLyxEXF/feZVVSUsL27duxefNmnDt3Djt37nzvPPnEOWfh4eEYO3YsWrdujV69\nesHExARRUVHs9kGDBuH69euorKxEeXk5rl+/DgsLCwwcOJC91rKyslBYWMi5rkTdN56enk0e8tSp\nUycAQH5+Pie87r2vo6ODrl27Nil/QgghXzaxBxSbmJggIyMDwLs3Er169cK+ffswfPhw1NTU4Jdf\nfuFMovwc8BsVVVVVqKyshJ2dndCJzaJERETAwsICenp6AIARI0ZAVlYWJ06cwNdff91s5TQwMEBM\nTAwnrFWrVo2mS0hIgJKSEtLT0/Htt9/i0qVLDa66xTAMpkyZgvDwcCxbtgwMwyAiIgJOTk6c4RkM\nw2DcuHFYvHgxJ3394VZr167F0KFD8eDBA3z//fc4ceJEox0gfmPrwIEDbIfM2dkZfn5+7L7FJS8v\njz59+uDixYtwdnbGpUuXsG3bNgDvJrtfvHgRxsbGSE9Ph6enJyetgoKCwFC++kNUBg4ciMDAQJSW\nliI0NBRRUVEoKipq8Il8TU0NIiMjsXLlSjbMzc0Ns2bNwrp16wTmmTQX/rngq62txYYNG9i3NU3B\nvy7fvn2LEydOYMOGDbh//z50dXXfu7yDBw9Gv379YGpqivbt2zcYd/z48bh69SoAoH379kIXAuBr\n7Jy9evUKx48fx9GjR9k0bm5u2L17N/tWxNLSEuXl5UhNTUVNTQ3U1NSgr68PHo+H+/fvo6ioCMnJ\nyVBQUECfPn3YfETdN2fOnMGiRYskO0D/T9Sbh4SEBLRp04b9nYY1/TeUlZUhOzu/8YgiZGdnN2Np\n/js+x3p9jnUCqF6fguZuq4vdkZgwYQL27t2L8vJyyMnJYcWKFRg7diy6desG4F0jKjIyslkL97Hx\nGxUtWrSApqamWBOY+aqrqxEVFYUnT55ATU2NDa+pqUFYWFizdiRkZGQafJMgip6eHlRUVNChQweU\nl5dj/vz5mDhxItvxEWbKlCkICAjAb7/9BiUlJWRnZwu8aQDePTVurEzq6urQ19eHvr4+wsPD0a9f\nPxw+fBhOTk4i09RtbMnIyEBTU5PTeTA0NERmZqbQtI8fP8br1685X2e3sLBAVFQU8vPzUVhYiP79\n+wN4d+4TEhLQpUsXVFVVCbyRYBim0frJycmxcTZu3Ig///wTixcvRmxsrMg0586dw6NHj+Dl5QUv\nLy82vKamBsePH2ePTevWrfHq1SuB9C9fvmTnF0iCfy7qUlJSYjsSampqUFZWFrkSGP+Y1z22da/L\nTp06IScnBwsWLMDVq1ebpeEqLS0t1j25bds2dhhmY5OxGztnMTExKC0thZ2dHSddTU0NUlNT0b9/\nf+jr60NXVxcpKSmora1lO+etWrVi50mkpKTA3NxcoPzC7ht1dfVG6ygK/7zUz5N/75P/Fnl5eRjr\nNu2PfHZ29mf3MA/4POv1OdYJoHp9qcT+az5lyhScO3eOXenF3NwcqampWL9+PTZs2IDLly9znmh+\nDviNCh0dHYk6EQDw22+/4cWLFzh//jzbcEhJScGhQ4dw4cIFFBQUfKBSN42zszO0tbURHBzcYDxd\nXV1YWVkhPDwc4eHh6NmzZ7MMizAwMICTkxO2bNnSaFx+Y0tLS0vgDYSTkxNycnKETooPDAyErKws\nHBwc2DALCws8ePAA4eHh6NWrF3t9Dxo0CFevXkVSUhI6der0Xo05Pj8/P5w/fx63bt0SGSc8PBz2\n9vacayY5ORmurq6cSb3GxsZCV41KT08XuYTn+5CSkoKjoyNiYmLw5MkTzraamhoEBwejc+fODV4L\nCxcuRE5ODuLj45u9fA3R1NRkO6ySznPhnzP+sQ4PD4e7u7vA+Rk2bBjn/PAn8vOHy/ENGjQIFy5c\nwKVLlwQ6px/Ctm3boKysLNGQTEIIIURcTXos+M8//+Dhw4eQlpbGmDFjMGrUKMjIyODBgwfNXb7/\nvL/++gt37tzh/JSXlyMsLAzDhg1D9+7dYWJiwv4MGzYMxsbGQlc/akhDkyOrqqpQVFSEwsJCzo8k\nGIaBl5cXIiMjG/0WyNSpU3Hy5EkcO3ZMYJI1v6ylpaUC5RG1Wg/fnDlzcPfuXZw+fVpknNra2gaP\nxddffw0HBwfMnj0b+/fvR15eHu7du4dVq1Zhz5498Pf3h6amJhu/b9++kJWVxe7duzkNPiMjI7Rq\n1YodniasHMKOubCPNPINGjQIX331FQIDA4VuLy4uxqlTpzBp0iTONdO5c2dMnToVKSkpyMvLAwDM\nnj0bZ8+eRUBAAO7du4e7d+9i7dq1uHHjBmbPni2yDO9j+fLl0NTUxNixY3Hq1Ck8fPgQ169fx+TJ\nk5GXl4cdO3Y0mF5fXx92dnYICgpiwxo7nw15n7Ti4p+zrVu34vfff8ft27fh5uYmcH6cnZ1x7Ngx\n/PPPPwDedSSuX7+OGzducK6fgQMH4ujRo3j69KnQidbvU5/nz5+jsLAQeXl5OHPmDJydnREfH48t\nW7YIrNAl7NqtrKxs8r4JIYR8mcQe2lRWVoaNGzciPDxcZEPzc/ognbhrutcf088wDOLj43H69GmR\nk0AdHBwQFRWFJUuWcNI1Vh5R4dnZ2eykyrrhxcXFIoeQCMvPxcUF/v7+2L17NxYvXixyn3Z2dlBW\nVkZZWRnGjx8vNO/IyEiBoW5mZmY4efKk0DwBoEuXLrC2tkZQUBCGDx8ustyNHat9+/Zh9+7d2Lt3\nL5YsWYIWLVqgZ8+eiI6OZpcu5pORkUH//v0FnhwD7xqRsbGxAg0+hmFQWloq9JjfvHkT+vr6Isvp\n7e0NT09P5OXlCQw3OXjwIGRlZQXKCAC9evViJ7ovW7YM/fr1Q0xMDDZt2oQdO3aAYRh06dIFcXFx\nIpdBbcqE3bpp2rRpg99++w0BAQHw8/PD33//DSUlJQwePBhnz57lvPoVtS9vb2/Y2toiJSUFgwYN\navB8inNPvM93F8TNz9vbGx4eHigvL4eRkRFMTU0F4vDnih09ehSurq6wsLBAZWUltLW1OefZzMwM\n5eXlUFJSEviQpSTHQlg8R0dHAO+Gx2hpaWHAgAFISkrifJCOn47/7Yq64bGxsRg8eLDQ/RNCCCHC\nMCUlJWI9ApszZw6ioqIwevRomJmZcSbq1TVlypRmLSAhhJCPy+p40ccuwhdhy4A26KnWtO+KfK7j\nuD/Hen2OdQKoXl8qsd9IxMfHw9XVVeSwDEIIIZ+nLQOEPzj6FJWVlUFeXv5jF0OodgqSzcUjYy4M\nEQAAIABJREFUhJCPTeyOBMMwAq/iCSGEfP6a+pT8vyg7O7/JKyMRQgjhEnuy9ahRo3D+/PkPWBRC\nCCGEEELIp0LsjoSvry/u37+PuXPnIi0tDU+ePMHTp08FfgghhBBCCCGfP7GHNvXt2xcAkJGRIXLp\n0s9p1SZCCCGEEEKIaGJ3JBYtWtRonOZcipEQQgghhBDy3yV2R+L777//kOUghBBCCCGEfEKa9GVr\nQgghhBBCyJeNOhKEEEIIIYQQiVFHghBCCCGEECIx6kgQQgghhBBCJEYdCUIIIYQQQojExF61iRBC\nyJfpVnHFxy5CsymTU8c/n1F9+D5UvdopSENTQbrZ8yWEfB6oI/GFKS4uhr+/P86cOYPCwkIoKyuj\nc+fO8PHxgZWVFQCgW7ducHd3x9y5czlp/f39ER8fj8uXLwMAvLy8cPDgQSxZsgQLFy5k4yUnJ8Pe\n3h65ublQUVFhw48fP46QkBDcuXMHVVVV0NPTw6hRo+Dp6Qk1NTUAQHl5OYKCghATE4OCggLIy8uj\nX79+WLRoEXr37s3mFRkZCW9vb/b3tm3bolu3bli6dCn69Okjsv75+fno0aOH0G1HjhyBjY0Nm/fg\nwYNx7NgxThwVFRWEhobC3t6ePVYPHz4UyMvHxwcrVqwQ2F/r1q1hYGCA2bNnY+LEiZw0lZWV2Llz\nJ2JiYpCTkwMpKSno6upi+PDhmDlzJs6ePYslS5YgJSUF+vr6bLqioiKYm5tj/vz5mDdvnsi6N6bu\nuZKXl4e6ujr69u2LGTNmwNzcnN3WXMfQ1tYWJiYm8PLy4lw/fHv37sXy5cuRmZmJ27dvs8e8vuvX\nr8PIyAj+/v7YtGkTgHfftOHxeOjbty9WrlwJY2NjkfXmX698ysrKMDExwYIFCzB06FA2vG7+dWlo\naODevXsAADs7O/b+4GMYBnl5eVBSUoKdnR1MTU0REBAAQPx7SJJjzlf/nli3bh2ioqJw+fJltGnT\nho137949DB48GLt27cLYsWOF7sPnconI4/dpevuxC/CBNH+9tgxoQx0JQohINLTpCzN16lTcunUL\nwcHBuHHjBg4dOoShQ4dyvkjOMIxYHxdkGAZycnLYtm0bnj171mDctWvXYvr06fjqq68QHR2N1NRU\nbNiwAfn5+di7dy8AoKKiAl9//TVCQ0OxaNEipKWlIS4uDjweDyNHjsSpU6c4eSooKCArKwuZmZmI\niYlBdXU1xo8fjzdv3jRa9qNHjyIrK4vzY2FhwW6XlpbG5cuXce7cuUaPgZ+fn0Bevr6+Qvd39uxZ\nmJmZwdPTE1euXGG38+v+448/YtKkSUhISMCVK1fw448/orS0FNu3b4erqysGDRqE2bNno7a2lk37\n7bffolOnTu/VieALCgpCVlYWrl27hm3btqFly5aws7PDtm3bBOK+7zGUkZGBs7MzoqKihG4PDw+H\ng4MDWrduzYalpqYK7LNDhw7s9o4dOyIrKwt3797FL7/8gvv37wt02ETh552YmAgtLS1MmTIFeXl5\nnDj8/Ov+1O04MAwDFxcXzvbMzEwoKSmx2+veW5LcQ0Djx1zUPVFaWorFixeDx+NxPi5aVVUFLy8v\nODg4iOxEEEIIIaLQG4kvSElJCa5evYpjx47B0tISAKCjo4OePXs2OU8LCws8evQImzZtwsaNG4XG\nuXHjBn766SesX78es2fPZsN1dHRgaWmJly9fAgB+/vlnpKam4vz58+jevTsbJzg4GC9evMDcuXNx\n584dyMvLA/jfU2cAUFdXh5eXFyZPnozs7GyRT2/5VFRU2LTCyMnJYdKkSVi5ciWsra0b7FgpKio2\nmFfd/fF4PCxbtgy7d+/GjRs32Cf9O3bswJUrV3D+/Hl069aNTaetrQ0zMzP2923btsHc3Bzbt2+H\nt7c3Dh48iOTkZKSkpDS4f3EpKyuzddHR0YGFhQU0NTWxevVqjB49GgYGBgJ1EkWcY+jq6oqff/4Z\nycnJnAZxRkYG0tPT4e/vz4nP4/E4b07qk5aWZsukoaEBV1dXLF68GC9evGgwXd28eTwefH19ERsb\nizt37nDe/tTNXxR5eflG49Qlzj3E19gxF3VPZGVloUePHti1axesra1x/Phx2Nvb46effsLTp08F\n3hoRQggh4qA3El8QRUVFKCoqIjExEW/fvv8r8NraWjAMg1WrVmH//v0CT2/5oqOjoaioCA8PD6Hb\nlZWV2XjW1tZsJ6KuefPmobi4GOfPnxeaR0lJCWJiYtCmTRvOE+r3sWjRIuTl5SE6OrrBeHXfDjSm\nsrISoaGhYBiG04E7fPgwbGxsOJ0IYXg8HrZs2YL169fj/PnzWLx4MdavXw89PT2xyyApb29v1NTU\nICEhQeK0jR1DExMT9OnTBxEREZzw8PBwGBkZcYZUAZId68LCQsTHx8PAwKDRTkTdvEtLSxEZGYmW\nLVsKvRbFzUfcuOLcQ00h7J4wMTHBsmXL4Ovri3PnzuHHH39EcHAwew8SQgghkqCOxBekRYsW2L59\nO6Kjo6Gnp4fhw4dj+fLluHHjRpPzZBgGw4YNQ//+/bF27VqhcXJzc6Gvrw9p6YbH2ebm5qJjx45C\nt3Xq1AkA8Ndff7Fhb968gY6ODrS1tWFgYID09HQkJCSww0gaMmrUKOjo6HB+Xr9+zYnD4/Hg7e2N\n9evXo7KyUmg+tbW1WLdunUBep0+fFrq/du3awd/fH/v378fAgQM5dTcyMuKk+eabb9j86jaox4wZ\nAwcHBzg6OsLMzAyurq6N1vd98J+CFxQUCK3T+x7DqVOnIj4+Hq9evQIAvH37FocPH8bUqVMF4nbv\n3p2zv65du3K2Z2ZmQkdHB1paWjAxMUF5eTni4uLEqmfdvGNiYhAbG8t5G1E3/7o/s2bNYrfX1tYi\nNDSUs73+MLf6xLmH+Bo75uLcE3PmzEGnTp3g5OQEV1dXdm4UIYQQIika2vSFsbe3x4gRI3DlyhVc\nu3YNZ8+eRXBwMJYvX47vvvtO4vz4T19Xr16NYcOGCUzQ5seR5CmtuBQUFJCSkoKqqipcunQJixYt\nQkZGBrp06dJo2j179sDU1JQTpqioKBBvzpw52LdvH3bv3o05c+YIbGcYBt7e3gKNXnV1dYH9de7c\nGdnZ2fD19cWZM2fg4ODQYBn9/f2xfPlyhIWFISYmhrPNz88Phw4dEjpJua4HDx7AzMyMHVbk6+sL\nHx+fBtMII+z8NdcxdHR0xNKlS3HkyBFMnz4dJ06cwD///INJkyYJxE1ISOBMFJaS4j4LMTAwQExM\nDN6+fYsTJ05gw4YNuH//PnR1dRutI7/BnZ6ejm+//RaXLl3idPbq5l9Xq1at2H8zDINx48Zh8eLF\nbFjdOR7CiHMP8TV2zMW9JxYuXIixY8dy5ksQIkxZWRmys/M/ahmys7M/6v4/hM+xTgDV61PQ0OIj\nTUEdiS+QrKwsrKysYGVlhUWLFmHevHnYsGED5s2bhxYtWqB169bs0+G6Xr58KfJpf69evWBvb4+V\nK1cKNG6NjIxw9epVVFZWomXLliLLZWhoyK5+Ux8/3NDQkA1jGIZ9YmxkZIQnT55gyZIlsLOza7Tx\npqWlJfC0WRhFRUUsWrQI69evh4uLi9A4KioqjealpaUFAwMDGBgYYOfOnRg9ejRcXFzY+Q+GhobI\nysripOF3RoQNy+E3oBt7y6OlpYVLly6xv9dthIvr2bNnKC4uFqhjcx3DVq1aYezYsYiIiMD06dMR\nHh6OESNGCJ0LoKen1+AwJRkZGbZMnTp1Qk5ODhYsWICrV68KdDpE5d2hQweUl5dj/vz5mDhxImfY\nWN38RVFSUhLruNTX0D3E19gxF/ee4B+LFi3oTwBpmLy8PIx1m7fhIYns7Oxmb/h8bJ9jnQCq15eK\nhjYRdOzYEVVVVSgvLwfwrrd6+/ZtgXjp6ekN3kwrVqzAlStXcPbsWU64k5MT3rx5g927dwtNx59s\n7eTkhAsXLiA9PV0gTmBgINTU1GBjYyNy/7Nnz0ZVVRV++eUXkXGaYtq0aVBVVcWWLVuaJb+BAwdi\n4MCBnPzGjx+PpKQkocf9fUhLS0NfX5/9aUpHIjg4GNLS0rCzs2tyORo7hq6urrh58yZOnTqFixcv\nNttwrYULFyInJwfx8fESpXN2doa2tjaCg4ObpRziEnUPNdWHuicIIYQQgN5IfFGeP38ONzc3TJ06\nFaamplBUVMTt27cRFBQEKysrdojE7NmzMXLkSAQEBGDMmDGora1FTEwMu/qSKAYGBnBzc8PPP//M\nCe/duzfmz5+PFStW4PHjxxgzZgy0tLSQn5+P8PBwGBoaws/PD15eXjh58iQmT56M1atXo1+/figp\nKcGuXbtw7tw5hIaGQk5OTuT+W7duDVdXV+zcuROenp4Nvv14/vw5CgsLOWHKyspC85eWlsby5cuF\nThavra3F69evBfKSl5dvcK6Gt7c3Jk+ejLt376Jz586YPXs2Tp8+DQcHB/j5+cHc3BwqKiq4f/8+\nEhMT/7UnxyUlJSgsLERFRQXu37+PAwcO4NChQ1izZo3Ak/DmOoYA0LdvX5iYmMDT0xPt2rXDsGHD\nhMYrKipCRQX3o1uqqqoiz7W+vj7s7OwQFBTU6FCyuhiGgZeXF1atWoXvv/8eqqqqAN4tl1pUVCQw\n1EtDQwNA48P4Gtsu6h7ik+SYA5LdE4QQQoik6I3EF0RRURH9+vVjh9YMGDAAa9euxYQJE7Bv3z42\nXr9+/RATE4Nz585h5MiRsLOzw7Vr1xAXF4fOnTuz8YR9b8LPzw8tW7YUCF+1ahX27duH9PR0TJgw\nAebm5vDz8wOPx8OMGTMAvBs2cuzYMbi6umLjxo3o27cvxowZg+LiYiQmJsLW1paTp7DlRD09PVFU\nVITDhw83eCwcHR1hYmLC+ambpn7eDg4O6Natm0A4wzDYtGmTQF51h6YIK6etrS2MjIzY7zPIyMgg\nLi4OCxYswMGDB2FnZ4f+/ftj0aJF+OqrrxAbGyuQhzjf+pDU/PnzYWJigr59+2Lu3LmoqqrCiRMn\nOB8642uuY8jn4uKCV69eYdKkSUKPMwCYmZlx9te5c2f2Ow6i8vX29satW7caXCJXWFoXFxfIysqy\nb9IYhkF2djY6deokUIaamho2TkPnRdh3JMS9hwDJjzkg+p74ENcPIYSQLwtTUlLS/LNgCSGEfDas\njhd97CKQj2TLgDboqSbz0fb/OY5P/xzrBFC9vlQ0tIkQQkiDtgyQfG7Nf1VZWRn7UcvPyYeqVzuF\nhhd0IIR82agjQQghpEEf84l0c8vOzv+oqxB9KJ9rvQgh/200R4IQQgghhBAiMepIEEIIIYQQQiRG\nHQlCCCGEEEKIxKgjQQghhBBCCJEYdSQIIYQQQgghEqOOBCGEEEIIIURi1JEghBBCCCGESIw6EoQQ\nQgghhBCJUUeCEEIIIYQQIjHqSBBCCCGEEEIk1uJjF+BzUlRUhB9//BGnT5/G48eP0bZtW3Tp0gXu\n7u4YNmwYAKBbt254+PAhAEBWVhZaWloYN24cvv/+e0hLSwMA8vPz0aNHDyQlJaFHjx4AABUVFXY/\nioqKMDIywnfffYcxY8YAAPz9/bFp0yYAgJSUFDQ1NWFjY4OVK1eibdu2bB6hoaGwt7cXKHtycrLQ\ncAC4fv06jIyMRNY7OTkZwcHBSEtLQ2lpKXR1dWFlZQVvb2+0b99eIG9lZWWYmJhgwYIFGDp0KBte\ntw51aWho4N69ewAAOzs7XL58WSCOo6Mj9uzZI7Se1dXVmDt3Lk6dOoWYmBj06tVLaD2ePXsGX19f\nnD9/HjU1NejSpQs2b96MLl26iKx7UVERTE1NsX37dkycOFFg+8qVK3HkyBFkZGQgKioKfn5+7PkH\ngNraWoSHhyM8PBz37t0DwzAwMDCAo6Mjpk2bhoEDB3Li1zdo0CDEx8cDANLS0rB582akpqaitLQU\nenp6cHR0xLfffgtZWVk2jTjXYEP13bJlC06fPo1Hjx6hdevW6NChAxwdHTFlyhS0atWKjStJedzd\n3TF37lyB/fHvBb5WrVpBU1MT5ubm8PDwaPDcAP+7XpYsWYKFCxdytk2fPh3Hjh3DzJkzERAQAADw\n8vLC8+fPcejQIQD/uyZdXFywbds2gXLVv0frXnf845yYmAhzc3M2rb+/P+Lj4znXcWVlJXbu3ImY\nmBjk5ORASkoKurq6GD58OGbOnAltbe0G63n8+HGEhITgzp07qKqqgp6eHkaNGgVPT0+oqakBAMrL\nyxEUFISYmBgUFBRAXl4e/fr1w6JFi9C7d+8G879VXNHg9k9JmZw6/vmM6sNH9Xo/7RSkoanQ8P9/\nhBBB1JFoJvn5+bC1tYWSkhJWrVqFrl27oqamBufPn4ePjw9+//13AADDMPDz88M333yD8vJyJCUl\nwdfXF3JycliwYEGD+wgKCoKtrS1KSkoQFBSEadOm4ddff0WfPn0AAB07dkRCQgKqq6uRnp6OuXPn\n4smTJ4iOjha7HqmpqZxOCwC2IyLM/v37sWDBAkycOBGhoaHQ09PD48ePERMTg82bNyMoKEgg76dP\nn2Lz5s2YMmUKUlNToa+vz8bh16Guuo1bhmHg4uKCFStWcOLUbZjWVV5ejhkzZuDOnTs4deoUOnbs\nKLIuK1asQFpaGg4dOgQNDQ1kZGSAYRiR8QFAXV0dtra2iIiIEOhIVFVV4eDBg5g2bZrIfDw8PBAf\nHw9fX19s2rQJampquHv3LkJCQqCmpoYLFy6guroaAJCRkQFHR0ckJSWxDcuWLVsCABITE+Hm5oaJ\nEyciLi4OqqqqSE1NxfLly3HhwgXExcWxcZt6DfKvcWVlZSxbtgxdunSBnJwc7t69i7CwMKiqqmL8\n+PFNKk9jx/no0aPo2rUrysrKkJmZiX379sHKygq7du3CuHHjRKZjGAba2tqIioridCSeP3+OxMRE\n6OjocPYtrCxycnI4cOAAvL290alTpwbLWX/fcnJyWLVqFX799VeR8SoqKjBu3Dj8/vvvWLx4MczM\nzMDj8fDgwQPExsYiODgY/v7+ItOvXbsWW7duhZeXF5YtWwZtbW3k5uYiPDwce/fuhZ+fHyoqKvD1\n11+joKAAq1evhpmZGZ4/f47du3dj5MiRCAsLg62trch9+FwuEbven4a3H7sAHwjVq6m2DGhDHQlC\nmoA6Es1kwYIFkJKSQlJSEhQUFNhwY2NjgQamoqIieDweAMDV1RV79+5FWlpao/tQVlYGj8cDj8fD\n1q1bcfToUZw6dYrtSEhLS7P5tmvXDp6enli/fj3evn0rsqFdH4/HE+hIiPLo0SP4+flh1qxZ2LBh\nAxuuq6uL/v374+XLl0Lz5vF48PX1RWxsLO7cucPpSNStgyjy8vKNxgGAV69eYdKkSSguLsavv/7a\n6FNdaWlp9O3bF/379wcATrka4urqCmdnZ+Tl5XHS/Prrr3j69ClcXFyEpouNjcXhw4cRHh6O0aNH\ns+H8J9EvX76EsrIyG84/L23btuXUv7S0FHPnzsWIESMQHBzMhuvo6MDIyAjW1tbYuXMn54l/U65B\nX19fSEtLIykpCfLy8mx4+/btMWLEiPcqT2P41w1/f8OGDcOsWbPg4+ODIUOGcI5TfcOGDcOJEyeQ\nnJwMCwsLAMChQ4fQp08fMAyD2tpaNm5tbS3ndwAwMDCArq4uVq1ahQMHDohdZgBwc3NDaGgo4uPj\n2beH9e3YsQNXrlzB+fPn0a1bNzZcW1sbZmZmDeZ/48YN/PTTT1i/fj1mz57Nhuvo6MDS0pK9B3/+\n+Wekpqbi/Pnz6N69OxsnODgYL168wNy5c3Hnzh3OeSWEEEIaQ3MkmsGLFy9w9uxZzJw5k9OJ4FNS\nUuL8zm+o1NbWIjk5GdnZ2ejZs6dE+5SWloa0tDTevhX9pEZGRgY1NTWorKwUO9/6jaiGHDt2DJWV\nlfDx8RG6vX7jjp93aWkpIiMj0bJlS7ZRIwlxyvj06VOMHj0aZWVlOHnyZKOdCAAYOXIkEhIScPr0\naYnKM3ToUGhqaiIyMpITHh4eDisrK+jq6gpNFx0dDWNjY04noq6GGsd1nT17Fs+fP8f8+fMFtn31\n1VcYPHgwDh8+zAmX9Bp8/vw5zp07h1mzZjXa2GxKeZrC29sbr169wvnz5xuM16JFCzg7OyMiIoIN\ni4yMhKurKwA0+jYEeDdE7fTp07hy5YpEZdTW1oa7uzvWrFnDvlmq7/Dhw7CxseF0IsQVHR0NRUVF\neHh4CN3Ov4aio6NhbW0t9H6bN28eiouLkZSUJPH+CSGEfNmoI9EMcnNzUVtb2+CwGb7a2lqsW7cO\nOjo60NDQgL29PWbPno1FixaJlRYA3r59i02bNuH169ewsrISGjcrKwv79u1Dnz59oKioKHZdunfv\nDh0dHfana9euIuPm5uZCSUkJGhoaEucdExOD2NhYgaf+mZmZnP3r6Ohg1qxZ7Pba2lqEhoYKxNm3\nbx8nnyVLluD169eIj4+Hqqpqo2W7d+8eZs+ejYMHD2L9+vU4cuQIu+3+/ftQUVFBbm6u0LRSUlKY\nNGkSDhw4wJ6jwsJCnD17lm2sCpObmwtjY+NGy9aYnJwcABB5/XXs2BF//fUX+3tTrkH+NV5/royp\nqSl7Dr777rsmlaep+MOMCgoKGozHHw6XkJCAf/75B7du3UJBQQHs7e3F7jibmprC2dkZK1eulKiM\nDMPAx8cHxcXFCAsLExonNzdX4Lh+88037HGtO79CWFp9ff1G57bk5uaKPB/848g/b4QQQoi4qCPR\nDCR5is8wDLy9vZGSkoITJ07AwsICiYmJDb5Z4PP09ISOjg60tLSwc+dOrFu3DkOGDGG38xvhmpqa\nMDMzg66uLkJCQiSqS0JCAlJSUtifxMREkXGFDQNpLO+LFy9i7969ePv2LS5duiQQx8DAgLP/lJQU\n/PDDD+x2hmEwbtw4gTj8sfl8tra2ePDgAXbu3ClW2TZs2ICRI0diyJAhOHjwINasWcOm/eOPP6Cp\nqYkOHTqITO/i4oLHjx/j3LlzAIADBw5AWVkZdnZ2Yu3/3/Q+12B9p06dQnJyMnr16tWk9O9Dkmuv\nY8eO6Nq1K2JiYhAeHo7x48dLPIxnyZIlyMjIYCe3i6tNmzb47rvvsHHjRpSWloqVxt/fHykpKXB3\nd8ebN29ExpP0HiSEEEKaE82RaAaGhoZgGAaZmZliNRxVVFSgr68PfX19hIWFoWfPnti+fTt8fX0b\nTLd27VoMHToUrVu3FjoB2sDAADExMeyqTfzJrJLQ09MTe46EkZERXr9+jSdPnqBdu3Zi592hQweU\nl5dj/vz5mDhxIvT09Ng4MjIyjc5NUFJSajSOo6Mj7O3t4eHhgerq6kbf+Pz5559wcnICAGhqaiIm\nJga2trZ4+vQp0tPTMXny5AbT6+vrw8LCAhERERgyZAgiIiIwYcKEBs+BoaEhMjMzG8xXHPyn2ffu\n3WPnd9SVmZkp8MRb0muwQ4cOYBgGWVlZnGu8ffv2AMBplBsaGkpcnqbgHztx57JMmTIFe/bsQX5+\nPmJjYwGIN6yJr+4wJUkWMAAAd3d37Nq1C9u3bxfYp6GhIbKysjhh6urqANDovWhkZISrV6+isrKy\n0WuNv/JZffxw/nkj5EtUVlaG7Oz8f21/2dnZ/9q+/k1Ur/++5hgJURd1JJqBiooKhgwZgpCQEHh4\neHCWwASAkpIStGnTRmjaNm3awMPDAz///DPmzJkDOTk5kftRV1dvsNEkTiO8OTk4OGD16tXYsmUL\nNm7cKLC9/mThupydnbFp0yYEBwezS282N0dHR7Ro0QIzZ85EdXU1vv/+e5FxNTU1kZyczK7sY2xs\njOjoaIwZMwYtWrQQGDoljKurK2bPno2EhATk5OQ0OKwJAJycnDBjxgyRE3EbOn512djYQFVVFUFB\nQQLzNG7fvo2LFy9i9erVItOLcw2qqqrCxsYGISEhcHd3F7jGgf+9IXjf8ohr27ZtUFZWFjm8r75x\n48ZhyZIlaN++vcglgBvj4+ODsLAwhIaGSpROVlYWS5cuhZ+fn8DiC+PHj8eaNWtw+/ZtzlK34nBy\ncsKuXbuwe/duzJkzR2A7/xpycnLC6tWrkZ6ejq+++ooTJzAwEGpqarCxsZFo34R8TuTl5WGs27wN\nLFGys7ObvTH3X0D1+jLR0KZmEhAQgNraWlhbWyMuLg7Z2dnIysrC3r17MWjQoAbTzpw5E2/evOFM\nBv1Q8vPzcefOHc7P69ev2e1FRUUoLCzk/IiarK2trY0ffvgBISEh8PLyQkpKCgoKCnDt2jUsXLhQ\nYInWuhiGgZeXFyIjI/H8+XM2vKqqSmgZ+Gpra1FaWiqw/cWLF0L34+DggP3792PLli1Yt26dyPLM\nnz8fly5dwrfffovff/8dGRkZOHPmDKSkpPD27Vv2CXZDRo8eDQUFBcydOxd9+vSBiYlJg/G//vpr\njBs3Du7u7ggICMDNmzdRUFCA3377DRMnTmxwWFldCgoKCAwMxOnTp+Ht7Y07d+7gwYMHOHLkCCZP\nngxzc3N4eXk1mIc41+DmzZtRU1MDKysrHDlyBPfu3cNff/2FmJgY/PHHH2jR4t1ziVatWklUntra\nWvz9998C12Xd6+L58+coLCxEXl4ezpw5A2dnZ8THx2PLli1o3bq1yDLXHfqjqKiIu3fv4rfffhO6\nXRz8YUriDpmry9nZGbq6ugLHePbs2TAzM4ODgwN27NiBW7duIS8vD0lJSUhMTGSPqzC9e/fG/Pnz\nsWLFCixduhRXr15FQUEBkpOT4e7uzpbTy8sL/fr1w+TJk9nvSNy5cwdz5szBuXPnsG3btgYfYhBC\nCCHC0BuJZqKvr48LFy7gxx9/xMqVK/H3339DVVUVpqamDa4BDwBqamqYOHEiduzYgW+++QaAZEMu\nJIlfv3HPMAwOHjzIrjZVf7lJhmEQGxuLwYMHC83vm2++gZGREbZv3w5XV1f2g3QDBgxKCTeYAAAg\nAElEQVTgrOYkrHwuLi7w9/fH7t27sXjxYjAMg+zsbIG1+hmGQXFxMaSkpMAwDCIjIwWedJuZmeHk\nyZNCyzh69GiEhYXBzc0N1dXVQifM2tjYID4+Hj/88APs7OzAMAwsLCzw66+/4sqVK1iwYAF0dXUb\nfGorKyuLCRMmICQkBFOnThUap/5x2Lt3L0JDQxEeHo7AwEBISUlBX18fo0aNEvqWQtR5Hj16NBIT\nE7F582bY29ujrKwMenp6cHNzg4+PT4ONUUDwGhS2H319fVy8eJFdbvTRo0do2bIlOnXqhJkzZ3Im\nxUtSHoZhsGPHDuzYsYOzv4CAAAwfPhzAu7dLwLunhlpaWhgwYACSkpIa/SBd/e9C1O901N8u7Pf6\nPDw8sHv3bjx69KjBfQsry+rVq9khdHwyMjKIi4vDzp07cfDgQaxbtw7V1dVo3749hgwZ0mgncNWq\nVejZsydCQkIQHh6O6upq6OnpwdraGjNmzGD3cezYMQQGBmLjxo0oKCiAnJwczMzMkJiY2OgH6Qgh\nhBBhmJKSEpqpRwghRCSr40UfuwiEfFBbBrRBTzWZf2Vfn+tQGarXl4mGNhFCCCGEEEIkRkObCCGE\nNGjLAOGLRXyKysrKPssveFO93k87hYa/xUIIEY46EoQQQhr0bw35+DdkZ+f/a6vz/JuoXoSQj4GG\nNhFCCCGEEEIkRh0JQgghhBBCiMSoI0EIIYQQQgiRGHUkCCGEEEIIIRKjjgQhhBBCCCFEYtSRIIQQ\nQgghhEiMOhKEEEIIIYQQiVFHghBCCCGEECIx6kgQQgghhBBCJEYdCUIIIYQQQojEWnzsAhBCCPlv\nu1Vc8bGL0GzK5NTxz2dUHz6q16fj365TOwVpaCpI/2v7I1+Wj9aR2L9/P5YtW4b8/Hy0aPGuGBUV\nFdDT04OBgQEuX77Mxs3NzUXv3r0RFxcHS0tLAEBRURG6dOkCDQ0NZGRkgGEYTv4ZGRn44YcfcPPm\nTbx8+RJqamro1asX1q9fj4sXL8Lb27vB8sXHxyM/P19oPIZh8OTJE8jIyAhsy8/PR48ePSAlJYX0\n9HTo6Oiw20pKSmBiYoK3b98iKSkJPXr04KRdtGgRQkJCEBgYCFdXV862yMhIeHt7Y/DgwTh27Bhn\nm4qKCkJDQ2Fvb88JDw4OxvLly+Hr64tly5YJlPX169fYtm0bW1dZWVno6enB3t4e06ZNg6qqKgDA\nzs6Ocz74HB0dsWfPHrYMAJCYmAhzc3M2TnV1Nbp27YonT57gl19+gYODAwCgW7duePjwoUCePj4+\nWLFiBXscVVRUcPv2bSgpKbFx7OzsYGpqioCAAHa/okyePBnbt28Xuq2kpASbN29GQkICHj9+DGVl\nZVhaWmLx4sUwNjZm4/n7+2PTpk0C6SMjIzFq1CiR+05OTkZwcDDS0tJQWloKXV1dWFlZwdvbG+3b\ntwcA1NTUICQkBOHh4cjJyUHLli3Ro0cPzJs3D0OHDuXkZW9vj9zcXJF1Pnv2LAIDA3H79m1UVlbC\n0NAQLi4u8PDw4NwfddMrKChAV1cXU6dOxZw5cwTybOga4pcJeHdPKCoqQldXFxYWFvDy8oKenh4n\nfnl5OYKCghATE4OCggLIy8ujX79+WLRoEXr37i3yOAL/u6/4WrVqBU1NTZibm8PDwwNdunQRWq76\nrl+/DiMjI/acuri4YNu2bQL7qX9/VlRUwMjICImJiejatSsbPnDgQPz5559IS0uDoaEhZ19eXl44\nePAgAEBaWhrq6uqwtLTEqlWr0K5dO07cxv4/q3u/yMvLQ19fHx4eHnBzcxN5zOqmkZWVhZqaGnr0\n6AEXFxfY2tpy4or6P4TP53KJyP18mt5+7AJ8IFSvT8e/V6ctA9pQR4J8MB9taJOlpSVKS0uRlpbG\nhqWlpUFZWRm5ubl49uwZG56cnAw5OTmYmZmxYQcOHICRkRFevXqFs2fPcvIuLi6Gg4MDWrdujejo\naFy/fh27du1Chw4d8Pr1azg6OiIrKwtZWVnIzMyElZUVxo0bx4ZlZWWhf//+AN41tOqG89MI60TU\npaWlhcjISE5YdHQ0eDyeQCMBAN6+fYvDhw+jT58+CAsLE5qntLQ0Ll++jHPnzjW4b76IiAj06dMH\nUVFRqKmp4WwrKSnB8OHDERUVhTlz5uDMmTNITk7G6tWrkZ2djYiICDYuwzBwcXEROA4//fQTJ08d\nHR1OOgA4c+YM21GsW2+GYeDn5yeQp6+vLyd9eXk5tm7dygljGIbNq27awMBAgbANGzYIPTb8+v/2\n22/YuHEjbt26hQMHDuDNmzewsbHBrVu3OPE7duwoUNa6Df369u/fj7Fjx6Jt27YIDQ3FtWvXsG3b\nNtTW1mLz5s1svJkzZ+KHH37AN998g6tXr+LMmTPo1asXJk6ciH379onMv749e/ZgwoQJ6NWrF06f\nPo3U1FTMnDkT/v7+mDVrlkD8oKAgZGVl4dKlS5gwYQKWLVuG6OhogXgNXUN8qampyMzMxMWLF+Hn\n54f09HQMHDgQly5dYuNUVFTg66+/RmhoKBYtWoS0tDTExcWBx+Nh5MiROHXqlFj1PHr0KLKysnD5\n8mX88MMPePr0KaysrHD06FGh5ap/zjp06MBul5OTw4EDB5CZmdnofpOTk6GiosLpRNy4cQPZ2dno\n3r07wsPDBdIwDANra2tkZWUhIyMD27dvR0pKCjw9PQXiNvT/GT8v/v1y6dIljBo1Ct9++63AQwVR\naW7cuIG9e/eiffv2cHFxwcKFCxutMyGEENKYj/ZGwtDQEJqamkhOTmY7CMnJybC0tERBQQFSUlLY\np9fJycno27cvp/EeEREBLy8vpKenIzw8nNOou3r1Kl6+fIkdO3awjVhdXV0MHDiQjSMnJ8f+W0ZG\nBnJycuDxeALlZBhGaHhjJk2ahKioKPj5+bFh4eHhmDx5stCn2/Hx8ZCXl0dISAh69+6Nu3fvonPn\nzpw4cnJymDRpElauXAlra2uhHRK+a9euIS8vDzdv3oS5uTnOnDmDESNGsNvXrFmDhw8fIi0tDRoa\nGmy4jo4OBg8e/H/t3Xk8Vun/P/DXTd2liSh3lD2UtMhEydq+KkyUylDfhoa0L9SktI2ophTty8cS\nhWhDD58UWUqmT+u00KKmRbcWFFnG7fdHv/vMfdy3dTRS7+fjcT96uM51n3O9zzn36VznWo7Y+mRk\nZOrdD9OmTcOuXbsQEBCA7777rt6YO3bsWO863dzcsGfPHri6uqJbt25iy0W/36lTJ7G02qxfvx4v\nXrzA1atXmfhVVFQQGRmJoUOHYu7cuaxWGGlp6QafB8+fP4eXlxdcXV1ZFRk1NTUMHjwYRUVFAIC4\nuDjExcWJtWz4+vqivLwcK1aswNixY9G9e/d6t7dy5UrMmTMHvr6+TPrMmTPB4/Hg5OSEiRMnMr8n\n4NO+4vF44PF4WLx4MdNyMmXKFCZPfeeQEI/Hg4KCAng8HjQ1NWFtbY0JEybA09MTV69ehZSUFHbv\n3o2srCykpKSgf//+AD6da0FBQXj37h3mzZuHmzdvQkZGps5YhdsBAHV1dYwaNQqurq5YtGgRRowY\nwZwDouWqjZaWFtTU1ODr64vIyMg6t5uQkCDW+hQWFgZra2uMGzcOPj4+8PHxgbT030/9qqurweVy\nmfJ269YNNjY2CAkJEVt/XdczIeHvhcfjYdWqVThx4gTi4+Nha2tba7lFf2MqKioYPHgwevXqhYUL\nF2LSpEmwsLCoM25CCCGkLi062Nrc3BxpaWnM3+np6bCwsKg1XSgzMxMvXryAg4MDXFxckJiYyGrB\nUFJSgkAgwIkTJ1BdXf3vBFPD6NGjUV5ejtTUVADAjRs38OTJE9jZ2UnMHxoaiunTp0NTUxMjR46s\ntVVi+fLlyMvLk/j0uOb6Jk2ahO7du2PKlCms9QkEAhw/fhxTpkxhVSLq0pD92KdPH/Ts2ZN5OlxQ\nUIDk5GTMmDGjyeu0tbWFvr4+fv311waVsyGE8Ts4OIjFz+Fw4Onpibt37+KPP/5o0vpPnDiByspK\nLFq0SOJy4c1uVFQUdHR0JHaPmj9/PioqKnDq1KkGb2/BggViyyZMmABtbW1ER0ez0oX7vqqqCnFx\ncXj37h0MDQ1Zeeo6h+oiJSUFDw8P5OXl4ebNm0ysw4YNYyoRNWN9/fo1Lly40KD11+Tp6Yni4mLm\ntybUkPNrzZo1SEpKwqVLl2rNU11djbNnz7KOU0lJCWJjY+Hi4gIbGxtUVFRIbFURLUNeXh6Sk5PF\n9nN917PacLlcVFQ0vp/1jz/+CHl5+QadW4QQQkhdWrwikZ2djcrKSpSVlSE7OxsWFhYwMzNjKhI5\nOTl49eoVMzYC+PQk0NbWFrKysvj++++hp6eHiIgIZrmxsTGWLFkCd3d3aGlp4YcffsBvv/2GP//8\ns9FlLCkpgaqqKutTs3+xJG3atIGjoyPTvSk8PBx2dnbo0KGDWN68vDxkZmbixx9/BAC4uLggKipK\n4k0Cj8eDp6cnNm7ciMrKSonb/vDhA06ePMn0n3ZxcUFSUhL4fD6AT12/iouLoaOjw/re6NGjmRgd\nHByY9OrqaoSEhIjth5pdb4RdoIQxHz16FEOGDGHGA4iqrq7Ghg0bxNaZlJQklnft2rWIjIzEvXv3\nJMbbWK9fv0ZRURF69uwpcbkw/cGDB0za/fv3WeU0NTWtdf2PHj2CnJxcvZW0hw8f1lqGbt26QVZW\nFg8fPqwvHDx8+LDO7enq6rJiAYCff/4ZqqqqUFJSgqurKwICAjBt2jRmeX3nUH169eoF4NOYA2EZ\na4tVmLchsTZkW0L9+/dnHTPRbklC+vr6cHR0xJo1a2pd/7Vr11BaWspq0Txx4gS6dOkCKysrcLlc\nODo6SqxoJScnQ1VVFd26dYOhoSE0NDTE8tV3PRMSVkr++usvHDlyBHfv3sXQoUNr3zG1kJKSgo6O\nDp4+fdro7xJCCCGiWnTWJktLS5SVlSErKwsCgQCKiorQ1NQEj8fD48ePwefzkZaWhg4dOsDIyAgA\nUFxcjFOnTrH6RLu4uGDfvn2YN28ek7Zq1SrMnTsXFy9eRHZ2NsLCwrB161ZERERI7LpTmw4dOiA9\nPZ2VVt/4CCEnJydYWlqCz+cjJiYG0dHREp+ShoeHw8LCghmcOmbMGLRr1w7x8fESWzDmzp2LQ4cO\nYd++fRIHyMbGxkJJSYm58enbty8MDAwQGRkp8am10H/+8x+Ul5dj06ZNePHiBZPO4XDwww8/wNvb\nm5VfOBhblL29PVatWoUHDx4gPDyc1bVLlPDJv7DyJNS1a1exvGZmZhgxYgRToWiJViYtLS3ExMQw\nfwu7zElSXV3doDLW1TWtudXc1vr16zFy5Ej8+eefWLFiBeLj41ljKZp6DgnVjL8xsdrb2+Py5csA\nPnVfkjTQv65tCZ05cwby8vLM31JSkp+brFy5EkZGRjh9+rTEFpOEhASMGTOG9f2wsDA4OTkxf7u4\nuMDMzAz5+fmsgdRmZmYIDAxEaWkpQkJCEBERAT6fz3S5auj1TFjx9vf3R3l5ObhcLhYsWICZM2fW\nuW9qU9t4F0LI1+fjx4/IzX1Sf8ZmkJub+69s59/2NcUlOplMc2jRioSmpibU1NSQnp6O6upq5qbl\nu+++w4ABA5Ceno709HQMGTKE6XscExOD0tJSTJgwgbUugUCArKwsZpA08Kk/tY2NDWxsbLBmzRpY\nWlpi8+bNjapIcDgcaGpqNik+HR0dGBgY4P/+7/+grKwMIyMjsaemVVVViIiIQH5+PhQVFVnxhIaG\nSqxIdOzYEcuXL8fGjRtZNzNCoaGhePTokdj6CgsLsWDBAigqKqJTp07IyclhfU/YF19OTg7Pnz9n\nLZOTk2vQfpCTk4O1tTUWLlyIgoICWFtb15pXQUGhwft2zZo1sLCwwKVLl/7xDbgw/tpaOISDb0Vn\n4eFyuQ0uq46ODt6/fy92U1mTtrZ2rQN9X7x4gffv34vNBFTb9oqLi/Hy5UuJ40ju378PfX19VlrX\nrl2hqakJTU1NhIWFYdCgQYiOjmZaouo7h+oj3LfCfaatrV3r/hamC2PduXMnyss/zWhSV4VNND7R\nbQlpaGjUO6sX8GnsgJubG9atWyexy2B8fDxWrFjB/J2Tk4OsrCxkZ2fDz8+PSRcIBDhy5AhrwoD2\n7dsz5fL398edO3fg7e2NuLg4AA2/nolWvGVkZBrcJVGSqqoqPHjwgHk4Qwj5usnIyEBXrXlvHiXJ\nzc1t9pvUL8HXGldzafEX0llYWCAtLQ1paWkwNzdn0s3NzZGamoqMjAyxbk1ubm5MJSM9PR1paWkY\nNWqUxJlThNq2bQsNDQ2UlpZ+1nhqcnJyQkZGRq3jBM6dO4d3794hJSWFFdOxY8eQmppaa3cs4fSs\n27ZtY6XfvXsXV69eRVxcHGt9ycnJePr0KTIzMyElJYUffvgBUVFRYhWG5vDjjz8iIyMD9vb2DW69\nqU/NLij/pFVCSkoKkydPRkxMDPLz81nLBAIBgoKC0Lt3b4ldYRrCxsYGXC5X7NgICQdbOzg44OHD\nh4iPjxfLExgYiHbt2rEGSNe1vbZt22LHjh1iy06fPo3Hjx+zuqrVpKWlBQcHB6a8DTmH6lJVVYU9\ne/agR48ezBN+BwcHpKam4saNGxJjVVRUxPDhwwF86tYlrOSITp9cm507d6JTp05N6uYjtGjRIrx+\n/VpsIPTjx4/x+PFj1uDnsLAwGBsbIyMjg7V/vLy8xGYtq8nLywspKSm4fv06s66GXs+EFe9/UokA\nPlUSi4uLG3RuEUIIIXVp8RfSWVhYIDo6GhwOB7t27WLSzczMMHPmTHz48IEZaH379m1cv34dwcHB\n0NPTY63H0dER8+bNw6ZNm5Ceno7Y2FhMnjwZ2trazGDJc+fOYeXKlRLLUduNaXV1Nfh8vthyHo9X\na1cJUdOmTcP48eNZ70EQFRoailGjRol1qdDT04Ouri7CwsIklllaWho+Pj6YM2eO2PoMDAwktrpY\nWVkhNDQUpqamWL16NTIyMjBq1Ch4e3vD0NAQHTt2xN27d5GRkcHqYlRdXY3S0lK8evWKtT4ulyvx\nia+FhQUePXrEzNwkSXV1Nd6/fy+2ThkZmVr3lbALCgCxJ+yN5ePjg9TUVNja2sLX1xd9+/bFy5cv\nsXXrVuTl5f2jgagqKir49ddfsWzZMhQXF2PGjBlQV1dHfn4+oqOjUVFRgcDAQNjZ2eHkyZPw8PCA\nr68vhg0bhrKyMhw9ehQHDhzAli1bxFoY/vjjD7H9069fP2zYsAHe3t5Mf30ZGRmkpKRgzZo1mDx5\ncr03jXPnzoW5uTmSkpJw4cKFBp1DQnw+HxUVFSgpKcHt27exe/du3L59G1FRUUzrkbu7OxITEzF9\n+nSsXbsWgwYNQmFhIfbu3Yvz588jJCSENZNabd6+fYtXr179/6b6XBw8eBDnz5/H3r17ISsry8or\nLJeozp07o23btmLrlZeXx+LFi7Fx40ZWenx8PKysrJixTZWVlTh69CiWLVsmdg2Sl5dHQEAALl68\nyHr4Icrc3BwGBgbYvn07li5dWu/1zN/fv87fUV1Ef2OVlZV4/vw5Tpw4gf3798PNza3OcT6EEEJI\nQ3wRFYnKykqoqKiwuiaYmJigrKwMcnJyzIuhQkNDoaOjI/EmcvTo0RAIBIiNjYWlpSU6duwIHx8f\nPH/+HNLS0tDU1MSGDRskzuEOSO7DzeFwUFpaygzmFE3/3//+V2tXF9F1SUlJid1sC5fz+XwkJSVh\nz549EtdjY2ODiIgIpltFzTLa2NggKCgIV69eBfBprv7o6GiJ4yaE+b28vLB582bIy8vj3LlzCAwM\nxK5du5guVz169MD48ePh7u7OKu+RI0fE3othYmKCxMREiduqr0sJh8NBQECA2LSwU6ZMwd69eyXG\nq6Kigjlz5kh88i663oYQxr9582Z4eXnh5cuXkJOTg5WVFZKTk1nNmE3pSjV79mzo6OggODgYzs7O\nzAvpTE1NWbM5Cce6HDx4ECtXrkSbNm1gaGiIqKgojBgxQqwMEydOFIv32bNncHNzg5aWFnbs2IFD\nhw6hsrISOjo6zLSw9enTpw+GDRuGLVu24PHjx/Dw8JCYT/QcEhJO3yx8IZ2lpSX27NnDeiEdl8vF\niRMnEBgYCH9/fzx9+pR5N0xCQkK9L6QTmjx5MoBPFc7u3bvD1NQUFy5cYL2QTrivRN87I0yPi4uD\nlZWVxGM6Z84c7Nu3j9VKFx8fzxqEnpiYiLdv30p8cZuysjIGDx6M8PBwWFpast53IsrT0xNz5sxB\nWVlZvdez48ePi72csqFEf2NcLheKioowNDREeHh4gyaMIIQQQurDKSwsbJn5UQkh5Av25s0b6Onp\n4c6dO016l8zXZOiphs3WRQj58mwzlYehYvN0M67L1zqW4GuNq7m0eIsEIYR8iQoLC/Hrr79+85UI\n4NONyNfi48eP9b74sDWiuFqPfzsm5Q7S9WcipImoIkEIIRJoa2s3aNasb8G/8TTz35Kb++RfmcHm\n30ZxtR5fY0zk29XiszYRQgghhBBCWh+qSBBCCCGEEEIajSoShBBCCCGEkEajigQhhBBCCCGk0agi\nQQghhBBCCGk0qkgQQgghhBBCGo0qEoQQQgghhJBGo4oEIYQQQgghpNGoIkEIIYQQQghpNKpIEEII\nIYQQQhqNU1hYWN3ShSCEEPLluva6oqWL0Gw+fvwIGRmZli5Gs6O4Wo+vMSaA4vonlDtIo1sH6c+6\njc+lTUsXoKW4u7vj6NGjAABpaWl07doVlpaW8PX1hbKyMivv77//ji1btiArKwulpaXQ0NDA5MmT\nsXDhQrRr146V9+bNm9i2bRsyMzNRWFgIFRUVmJiYwNPTE/r6+njy5AkGDBiACxcuYMCAAQCA0tJS\nODs7Izc3F4MHD0Z6ejoyMzMhLy/PrPfevXuwsrLC3r17YWtrKxaPn58fAgICYGlpiZMnT7KWHTx4\nEEuXLkXv3r2RmZnJpJeVlWHHjh2IiYnB06dPISMjg0GDBmH58uUYOHAga92nT59mfReAWCxpaWmY\nNGkSdHV1cenSJUhL//2j6NevH9zc3GBjYwMDA4M6j423tze8vLwAAGZmZrhz5w5+//13aGtrs/K5\nu7vj7du3OHbsGGsfODk5YefOnbWWsy58Ph99+vSBkpISbt26BQ6Hw1rer18/PHv2DADQrl07dO/e\nHT/88ANWrFjBivfMmTMIDAxETk4Oqqqq0L17d5iYmGDHjh0AwOwrSbKzs6Gjo9OkeJYvX479+/cj\nMDAQzs7OrGVHjhyBl5cXU/76CMv46NEjKCgoiO0HNzc3zJs3DwCQnp6OgIAA/PHHH/j48SOUlJRg\nbGyMrVu3QlZWlvXdoKAg+Pj4YMmSJVi1apXEbQp16tQJenp6WLp0KUaOHMmkN+Z8Dw0NxcqVK5Ge\nng5NTU0mH5/Px5AhQ7BgwQLMnz+/1v1w/PhxbN++HWlpaWLLhMeipgkTJiA8PFxsuaysLLS0tODh\n4YGpU6eKfe+fHD/Ra5ooY2NjnDx5EhYWFrCyssLWrVtZyzds2ICIiAixa46oRZmFEtNbr/KWLsBn\nQnG1Hl9jTADF1TTbTOVbbUXim+3axOFwMGzYMOTk5ODWrVsIDg5Geno6fv75Z1a+hIQEjBs3DoqK\nijh58iSuXr0KLy8vhISEwM7ODpWVlUzes2fPYuTIkSgtLcW+ffuQnZ2NQ4cOQVlZGWvXrpVYjsLC\nQtja2uLly5dISkrCrl27wOPxsHz5cibPX3/9BXd3d9jY2EisRAjjUVJSQlZWFp4+fcpaFhYWBlVV\nVVZaRUUF7OzsEBISguXLl+P333/HyZMnwePxMG7cOJw9e7ZR+1PUs2fPEBYWJlY+DocDVVVV5OTk\nMJ/ly5dDRUWFlebp6QkAuHr1KnJzc9G/f3+x9YmuU1T79u0RGRmJ+/fvN6nskZGR0NHRQXFxMZKT\nkyVu08vLCzk5OcjOzsbChQsRGBiIbdu2MXlSU1Mxa9YsjB8/HsnJyUhLS8O6deskbi8rK4sVe05O\nDnr06NGkeMrLyxEdHQ0jIyOEhoY2IfqGE9339+7dg729Pfr164czZ87g0qVL2LZtGzp16oSKCvEn\n2eHh4TAyMkJERAQEAoHE9Qv3S0JCArp3744ZM2YgLy+Ptf2Gnu/Ozs4wNzeHh4cHqqv/boBduHAh\nevXqVWclAvh0DbC2tq4zT2xsLOsY7tq1S+Ly5ORkmJiY4Oeff8alS5dYef7p8RO9pol+oqKiICMj\ng7179yI0NBQpKSnMd65du4YdO3YgODi41koEIYQQUptvtiJRXV0NLpcLHo+Hbt26YdiwYbCxscHv\nv//O5CktLcW8efMwZswYBAUFoX///lBVVcXkyZMRGRmJy5cvY8+ePUzeuXPnYuTIkTh27BisrKyg\nrq6OAQMGYPXq1di3b59YGV6+fIlx48ZBWloaCQkJUFJSQps2bbB3716cPn0ap06dAgD89ttvKCgo\nwObNm+uMp3Pnzhg9ejSOHDnCpN++fRsPHjyAjY0NK//u3buRlZWFyMhI2NvbQ1VVFf3790dQUBBG\njRqFefPm4ePHj03at3PmzMGmTZtQWloqtkxKSgo8Ho/5dOzYUSztu+++A/DphtDa2hqenp44evQo\nqqqqxGIWvTEEAC0tLYwYMQK+vr5NKnt4eDhcXV1hZ2cnsfICAB07dgSPx4OamhqcnZ2hr6/POm8S\nExNhZGSERYsWQUdHB1paWhg7dizTGiFKNG7hR0rq759lY+I5ffo0ZGRksH//fly7dg13795t/A5o\ngvPnz6NLly7YuHEjevfuDQ0NDQwdOhSbN29Gly5dWHmvXLmCvLw8hISEoKSkBP/9738lrlO4L/T1\n9bFkyRJUVFTg5s2bzPLGnu87d+5ETk4OgoODAQBHjx5FWloadu/eXWdslZWVOJKmE+cAABW7SURB\nVHfuHMaPH19nPgUFBdYxlJOTk7hcV1eXaYW5evUqK88/PX6i1zTRj7CCMHDgQCxcuBCenp4oLi5G\neXk53N3d4eLigmHDhjVqW4QQQgjwDVckALBuQvPy8pCcnAxDQ0MmLTk5GW/fvsWCBQvEvmtgYAAr\nKytER0ez8i5atEjitjp16sT6++HDhxgzZgzU1dURFxfHWq6np4dVq1ZhyZIlOH/+PLZu3YqgoCCx\ndUji5OSEyMhI5u+wsDDY2dmhY8eOrHxRUVEYNmwY+vfvL7aO+fPn4/Xr16wnl43h6uqKNm3aMDdt\nTVFSUoLY2Fi4uLjAxsYGFRUVDW4lWbNmDZKSksSe+NYnMzMTL168gIODA1xcXJCYmIg3b96I5ROe\nN9XV1UhLS0Nubi7rvFFWVkZOTg5u375d7zZrVoQkaWg8oaGhmD59OjQ1NTFy5MjP3iohpKysjNev\nX0vs+lNTaGgoJk2ahO7du2PKlCm1llG4X0pLS3HkyBG0bdtW4rna0POdx+Nh27Zt2LhxI1JSUuDt\n7Y2NGzdCQ0OjzvKmpaVBTk4O/fr1qze2hqisrERISAg4HA7rnAGa5/jVdz55eXlBUVERXl5e2LBh\nA6qqqrB+/fpGb4cQQggBvvGKRHJyMlRVVdGtWzcYGhpCQ0OD9Z/3w4cPAQA9e/aU+P2ePXviwYMH\nAIBHjx7VmbcmDw8PqKioICIiAu3btxdbPnfuXPTq1QsODg5wdnbG0KFDG7TekSNH4q+//kJKSgrT\nVcLJyUnsBuPRo0e1lrVXr14AwMTWWDIyMvjll1+wc+dOvH37tknrOHHiBLp06QIrKytwuVw4Ojo2\n+MZKX18fjo6OWLNmTaO2GRYWBltbW8jKyuL777+Hnp4eIiIiWHmqq6uxYcMGqKqqQklJCZMmTYKH\nhwerK5qbmxuMjIxgYWGBvn37wsXFBYcPH0ZJSYnYNoWtXMJP3759mxRPXl4eMjMz8eOPPwIAXFxc\nEBUVJbFrUXOztbWFvb09Jk2ahJ49e8LR0RHBwcFilbAPHz7g5MmTcHFxYcqYlJQEPp8vtk7R/RIT\nE4O4uDjW+Aahhp7vADBx4kTY2Nhg8uTJMDExERuDIElCQgImTJhQb77x48ezjuPly5clLldWVoaf\nnx8OHz4MMzMzZnlzHT/hNU30I9qtUtjiGRcXh3379mHPnj0Srz+EEEJIQ3zTFQkzMzOkp6cjOTkZ\nbm5uyMzMlHhTUxdhP/GGPFkWNWHCBGRnZyMmJqbWPMuWLYNAIGDdpNZHSkoK06ZNQ3h4OOLj48Hj\n8TB48OBGla05ODo6Qk1NDf7+/k36flhYGJycnJi/XVxckJycjPz8/AZ9f+XKlbh16xZOnz7doPzF\nxcU4deoU6+bSxcUF4eHhrHwcDgeenp5IT09HfHw8LCwskJCQgPLyvwdidejQAceOHcO1a9ewfPly\ndOrUCWvXroWJiQkKCgpY6ztz5gzS09OZT0JCQpPiCQ8Ph4WFBfOEfcyYMWjXrh3i4+MbFP8/ISUl\nheDgYNy5cwfr16+Hmpoadu7cCWNjY9y7d4/JFxsbCyUlJeYGum/fvjAwMGC1KAidOXMGFy9exMGD\nB1FeXo6MjIxat92Y893LywsCgQDLli1rUGxnz56tt1sTABw4cIB1HGsOwD5w4ADS0tIQGRmJzp07\ni3Xpaq7jJ7ymiX6EA+KFevXqhUmTJsHS0pI1qQIhhJCW8fHjR+Tm5v4rn+b2zc7aBHwayCp8yunv\n7487d+7A29sbcXFxAAAdHR0AnwaTSro5uX//PjOTkPDf+/fvY9CgQfVue/78+RgwYAA8PDxQVVWF\n6dOni+UR9pVv06Zxh2nGjBkwNTXF06dPMWPGDIl5tLW1WTd5ooTpwphkZWVRXFwslq+oqAiAeLct\n4NMNt6+vL2bMmAF3d/dGlT8nJwdZWVnIzs6Gn58fky4QCHDkyBEsWbKk3nWoqKjAzc0N69atQ1RU\nVL35Y2JiUFpaKvb0WSAQICsri3X8FRQUoKmpCU1NTYSGhsLQ0BDBwcFi5RLmcXZ2xpIlS2BkZISD\nBw/C29ubyaOhoSE2I1Jj46mqqkJERATy8/OhqKjIKntoaCjs7OzqXb8kwtmWioqKxMpYVFQkNg6g\nW7dumDp1KqZOnYpffvkFRkZG2LFjBzPwODQ0FI8ePRIrY2FhoVj3QeF+6dGjB8rKyrBgwQJMnTpV\nYlekhpzvQsLflOgMW7W5du0aPnz4AHNz83rzdu/eXWKLiehyLS0taGlpYc+ePbC2toaTkxNMTEya\n9fiJXtPqIi0tzRqLQwghpOXIyMhAV023pYvRJPQ/iQgvLy+kpKTg2rVrAIDhw4ejc+fOEgfJXr9+\nHRcvXoSDgwMAYMSIEejSpQtr9h5RhYXi0yfOnz8f69evx7x582od2NsUPXr0wMCBA3H9+nVMmzZN\nYh4HBwekpqbixo0bYssCAwOhqKiI4cOHAwB0dXWRn5+PV69esfLduHEDXC631n7mo0aNwuDBg2ud\nsag2YWFhMDY2RkZGBuvJqpeXl1gLQV0WLVqE169fIyQkpEHbdHNzY20vLS0No0aNqvPYyMvLY86c\nOdi9ezfKyspqzaeurg4ZGRmJA9AbqrZ4zp07h3fv3iElJYVV/mPHjiE1NRV//vlnk7anra0NKSkp\nXL9+nZWel5eH4uJi6OrWftGTl5dH165dmXjv3r2Lq1evIi4ujlXG5ORkPH36VGxqYVGOjo5QUVFB\nUFCQxOUNOd+bIj4+HmPGjGn2G24zMzOYmZkx14rmPH41ZzFrrryEEEKIJN90i0RN5ubmMDAwQGBg\nIP7zn/+gQ4cOCAwMxKxZs+Dp6Qk3NzcoKCjgypUr8PHxwZAhQ5in7R06dMCOHTswc+ZMTJ06Fe7u\n7tDS0sK7d+9w5swZ3Lp1i3nfgSgPDw+0bdsWCxcuRFVVFWbOnNksscTExKCioqLWAdru7u5ITEzE\n9OnTsXbtWgwaNAiFhYXYu3cvzp8/j5CQEKbv9MiRI9GzZ0/Mnj0bPj4+UFJSwo0bN/Drr7/Cw8Oj\nzhutdevWYcSIEeByuQ0qd2VlJY4ePYply5ZBT0+PtUxeXh4BAQG4ePEiLC0t612XvLw8Fi9ejI0b\nN9aZ7/bt27h+/TqCg4PFtuno6Ih58+bB39+fmU2qpp9++gmBgYEIDw/HTz/9BD8/P5SVlWHUqFFQ\nVVVFUVER9u7di9LSUowbN471XT6fL9YPvnPnzmjbtm2D4wkNDcWoUaPEBiPr6elBV1cXYWFhWLly\nJYBPT7lv3brF6orXpk0b6Ovri21PVlYWzs7O8PHxAZfLhb6+Pp4/fw5fX18MGjQIQ4YMAQAcPnwY\nt2/fhrW1NTQ1NVFWVoajR4/i7t27WLx4MVNG4QQFNVlZWSE0NBSmpqYS9y+Hw4G7uzt8fX2xYsUK\ndO7cWSxPfed7UyQkJDDvM2lunp6emD59Ou7evdusx6+8vBx8Pp+1XFpamtXSIdTY7piEEEJITd9s\ni4SkdxAAn/6DP3PmDDNnvbW1NRISElBQUIBJkybByMgI/v7+cHFxQVxcHKvb0fjx45GUlAQZGRm4\nublh0KBBmDVrFp48ecJ68VbN7bq6umLLli1YsmQJDh06JFbOhsYjSkZGhnVTVXM5l8vFiRMn4Ozs\nDH9/fxgbG2PixIl4/fo1EhISMHbsWCavtLQ0YmNjoa6uDldXV5iammLTpk1wd3cXe6FYze0YGhrC\n1ta2zkGjot9JTEzE27dvJb6sTVlZGYMHD2ZaJWoeQ0n7as6cOeDxeHXux9DQUOjo6Ei8mR49ejQE\nAgGOHz9e6/cVFRUxdepU7Nq1CwKBAObm5njy5Anc3d1hYmICe3t7PHv2DJGRkczNt7A8JiYm0NPT\nYz6iLw1sSDx8Ph9JSUli050K2djYICIiAtXV1eBwOPj48SMsLS1hZWXFfGp7MR4AbNq0CU5OTli7\ndi1MTU3h4eGBvn37sl58NnDgQJSWlmLx4sUwNTXFhAkTcOnSJezduxf29vaoqKhAdHR0nWU8ffo0\n3r9/X2vcTk5OaNeuHTONcmPPd1EN+U3l5eXh0aNHrJfgNXV9kpaPHTsWOjo6WL16Nf773/82y/Hj\ncDhISUlBr169WOeUpIkaarv+EUIIIY3BKSwspMdShBAiIjg4GBcvXpTYivgtGnqqcZNQEEIIabht\npvIwVGxYz40vDXVtIoSQGlRUVGp9J8y3aJvp1/PW648fP0JGRqali9HsKK7W42uMCaC4/gnlDvVP\nAPKlohYJQggh34zc3Nw6JwporSiu1uNrjAmguL5V3+wYCUIIIYQQQkjTUUWCEEIIIYQQ0mhUkSCE\nEEIIIYQ0Go2RIIQQQgghhDQatUgQQgghhBBCGo0qEoQQQgghhJBGo4oEIYQQQgghpNGoIkEIIYQQ\nQghpNKpIEEIIIYQQQhqNKhKEEEJYDhw4gP79+0NZWRlDhw7FpUuXWrpItcrIyICjoyP09fWhoKCA\niIgIsTx+fn7o3bs3unXrBmtra9y7d4+1vLy8HMuWLYO2tjZUVFQwbdo0vHjx4t8KQaLffvsNw4YN\ng7q6OnR0dODo6Ii7d++K5WtNse3fvx9mZmZQV1eHuro6Ro8ejaSkJFae1hRPbX777TcoKChg2bJl\nrPTWFpufnx8UFBRYHz09PbE8rSkmAMjPz8fPP/8MHR0dKCsrw8TEBBkZGaw8rS2ufv36iR0rBQUF\nTJ06FQBQXV392WKiigQhhBBGbGwsVqxYgaVLlyItLQ2DBg2Cg4MDnj171tJFk6i0tBR9+/aFn58f\nZGRkwOFwWMu3b9+OXbt2ISAgAOfPnwePx4OdnR0+fPjA5FmxYgXOnDmDQ4cOISEhAe/fv8fUqVMh\nEAj+7XAYGRkZcHV1RVJSEk6dOoU2bdrA1tYWhYWFTJ7WFpuKigrWrVuHixcvIiUlBZaWlpgxYwZu\n3brVKuORJDs7GyEhIejTpw/rXGytsfXs2RM5OTnMJzMzk1nWGmMqLCzEmDFjwOFwEB0djStXriAg\nIAA8Ho/J0xrjSk1NZR2n1NRUcDgc2NnZAQACAwM/W0z0HglCCCGMESNGoF+/fti+fTuTNnDgQNjY\n2GD16tUtWLL6qaqqYvPmzZg2bRqAT0/h9PT0MGfOHCxevBgAUFZWBl1dXaxfvx4zZ85EUVERdHV1\nsWvXLtjb2wMAnj9/jn79+iEmJgbDhw9vsXhElZSUQF1dHRERERgzZsxXE5uWlhZ8fX3h7Ozc6uMp\nKirC0KFDsXPnTmzatAn6+voICAhotcfKz88Pp0+fZlUehFprTOvWrcOlS5eQmJgocXlrjaumLVu2\nICgoCPfv3weXy/2sMVGLBCGEEABARUUFbty4gWHDhrHShw8fjqysrBYqVdM9efIEfD6f9Z9g+/bt\nYWpqysRz/fp1VFZWsvKoqKigV69eX1TM79+/h0AggLy8PIDWH1tVVRWOHz+O8vJymJqatvp4AGDh\nwoWwtbWFubk5qqv/fkbbmmPLy8tD7969YWBggNmzZyMvLw9A640pPj4e33//PWbNmgVdXV1YWFhg\n//79zPLWGpeo6upqhIWFYcqUKWjXrt1nj6nN5wmDEEJIa/PmzRtUVVWha9eurHRFRUXw+fwWKlXT\nvXr1CgBY3RaAT/Hk5+cDAPh8PqSlpdG5c2dWHh6Ph4KCgn+noA3g7e2N/v37Y9CgQQBab2x//PEH\nRo8ejfLycsjIyODw4cPQ1dVlblZaWzxCISEhyMvLw4EDBwCA1a2ptR4rY2Nj7N69G7q6uigoKMDm\nzZsxZswYXL58udXGlJeXh4MHD2Lu3LlYvHgxbt68CS8vLwCAq6trq41L1IULF/D06VO4uLgA+Pzn\nH1UkCCGEfHNqjqX4kq1cuRJXrlxBYmJig8r9JcfWs2dPZGRkoKioCCdPnsTs2bNx+vTpOr/zJccD\nALm5uVi/fj3Onj0LaWlpAJ+eCou2StTmS45t5MiRrL+NjY1hYGCAiIgIGBkZ1fq9LzkmgUCAgQMH\nwsfHB8CnQcqPHj3CgQMH4OrqWud3v+S4RIWEhGDgwIHo06dPvXmbIybq2kQIIQQA0KVLF0hLS4u1\nPhQUFEBJSamFStV0wjLXfKJWUFDAtLp07doVVVVVePv2LSsPn88Xa5lpCStWrEBcXBxOnToFDQ0N\nJr21xta2bVtoamrCwMAAq1evhpGREfbv399q4wGAK1eu4M2bNzAxMYGioiIUFRWRmZmJgwcPgsfj\noUuXLgBaZ2yiOnToAD09PTx+/LjVHi9lZWX06tWLlaarq8tMJtFa4xIqKChAYmIinJ2dmbTPHRNV\nJAghhAAAuFwuBgwYgAsXLrDSL1y4gMGDB7dQqZpOQ0MDSkpKOH/+PJNWVlaGy5cvM/EMGDAAbdu2\nZeV5/vw5cnJyWjxmLy8vphKho6PDWtbaYxOqqqqCQCCApqZmq43H2toaly5dQnp6OtLT05GWlgZD\nQ0PY29sjLS0N2trarTY2UWVlZcjJyYGSklKrPV4mJibIyclhpT148ADq6uoAWv/vKiIiAu3bt2cG\nTAOfPyZpb29v3+YNgxBCSGslKysLPz8/KCkpoX379ti8eTMuX76MoKAgyMnJtXTxxJSUlODevXt4\n9eoVwsLCoK+vD1lZWVRWVqJTp06oqqrCtm3boKOjg6qqKvzyyy/g8/nYvn07uFwu2rdvj/z8fBw4\ncAB9+/ZFUVERFi1ahE6dOmHt2rUt1p1h6dKlOHbsGA4fPgwVFRWUlJSgpKQEHA4HXC4XHA6n1cXm\n6+uLdu3aQSAQ4Pnz59i9ezeio6Oxbt06aGlptbp4hNq3b8+0RCgqKoLH4yEqKgpqamqYPn16qzxW\nALBq1SrmeD148ADLli3D48ePsX37dsjJybXKmNTU1ODv7w9paWkoKysjNTUVGzZswOLFi/H999+3\n2mMFfOpON3fuXIwdOxYTJ05k0j93TDRGghBCCMPOzg5v377Fli1b8OrVK+jr6yMqKgqqqqotXTSJ\n/ve//2HSpEkAPv2H6efnBz8/P0yfPh3BwcFYsGABPn78iGXLlqGwsBBGRkaIjY3Fd999x6zDz88P\n0tLSmDVrFsrKymBlZYV9+/a1aJ/ogwcPgsPhwMbGhpXu7e3NDA5tbbHx+Xy4ubmBz+dDTk4Offv2\nxfHjx5lZwlpbPHXhcDisMrXG2F6+fImffvoJb968gaKiIoyNjXHu3DnmWtAaYzI0NMSRI0ewbt06\nbN68GWpqali1ahVmz57N5GmNcQFAWloaHj9+zAz4F/U5Y6L3SBBCCCGEEEIajcZIEEIIIYQQQhqN\nKhKEEEIIIYSQRqOKBCGEEEIIIaTRqCJBCCGEEEIIaTSqSBBCCCGEEEIajSoShBBCCCGEkEajigQh\nhBBCCCGk0agiQQghhBBCCGk0qkgQQgghhBBCGu3/AQ6XiX35yN68AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b336310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_PM25 = top_PM25.set_index(\"name\")\n",
    "top_PM25.plot(kind=\"barh\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at that! If you want the bars to be sorted from highest to lowest, you just need to sort the new data frames with `ascending=True`. Remember how?\n",
    "\n",
    "But now I want to make a double bar chart with the top VOC emitters and also how much particulate matter each of those guys emit. Let's quckly make a new data frame with both columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VOC</th>\n",
       "      <th>PM25</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>METAL CONTAINER CORP</th>\n",
       "      <td>245.766000</td>\n",
       "      <td>3.312178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENCANA OIL &amp; GAS - HIGH MESA COMP STATIO</th>\n",
       "      <td>262.566680</td>\n",
       "      <td>1.988200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KMCGEE FT LUPTON/PLATTE VALLEY/LANCASTER</th>\n",
       "      <td>276.600380</td>\n",
       "      <td>13.780000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUNCOR ENERGY - DENVER REFINERY</th>\n",
       "      <td>315.179760</td>\n",
       "      <td>240.506849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENTERPRISE GAS PROC - MEEKER GAS PLANT</th>\n",
       "      <td>317.662263</td>\n",
       "      <td>26.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WPX ENERGY - RULISON WATER MANAGEMENT</th>\n",
       "      <td>320.154475</td>\n",
       "      <td>0.266380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLORADO INTERSTATE GAS CO  CHEYENNE STN</th>\n",
       "      <td>350.370000</td>\n",
       "      <td>14.871976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MILLERCOORS; LLC - GOLDEN BREWERY</th>\n",
       "      <td>570.930000</td>\n",
       "      <td>36.710164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Denver Intl</th>\n",
       "      <td>625.585141</td>\n",
       "      <td>70.283926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WPX ENERGY LLC - PARACHUTE WMF</th>\n",
       "      <td>698.871541</td>\n",
       "      <td>0.166440</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 VOC        PM25\n",
       "name                                                            \n",
       "METAL CONTAINER CORP                      245.766000    3.312178\n",
       "ENCANA OIL & GAS - HIGH MESA COMP STATIO  262.566680    1.988200\n",
       "KMCGEE FT LUPTON/PLATTE VALLEY/LANCASTER  276.600380   13.780000\n",
       "SUNCOR ENERGY - DENVER REFINERY           315.179760  240.506849\n",
       "ENTERPRISE GAS PROC - MEEKER GAS PLANT    317.662263   26.400000\n",
       "WPX ENERGY - RULISON WATER MANAGEMENT     320.154475    0.266380\n",
       "COLORADO INTERSTATE GAS CO  CHEYENNE STN  350.370000   14.871976\n",
       "MILLERCOORS; LLC - GOLDEN BREWERY         570.930000   36.710164\n",
       "Denver Intl                               625.585141   70.283926\n",
       "WPX ENERGY LLC - PARACHUTE WMF            698.871541    0.166440"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_VOC = df[[\"name\", \"VOC\", \"PM25\"]].sort(\"VOC\", ascending=False).head(10).set_index(\"name\")\n",
    "# Re-sort the data frame inplace so the new sorting order is saved to top_VOC\n",
    "top_VOC.sort(\"VOC\", ascending=True, inplace=True)\n",
    "top_VOC"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we'll set the bar chart to a variable so we can customize it in all sorts of ways."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vhERFRSmdc76+vqI6f/31F+Lj45WOU53fw4kTJ5CVlYWff/4ZPj4+mDZtmuhi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Nb5X6UsJtHR0YiNjVX5aEEvLy8EBwdj6dKl8qHV6pxPWR1BEJCfn6/wDHpBEPDLL7+UOuTbwsIC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109611190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "VOCchart = top_VOC.plot(kind=\"barh\", figsize=[10, 6], width=0.6, color=[\"cornflowerblue\", \"#FFA07A\"], edgecolor=\"k\")\n",
    "# width refers to the width of each bar\n",
    "# Colors can be defined by CSS name, hex code, or one-letter abbreviation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See how it added a different bar for each column in the data frame? And look at all the other options we can call directly within the `plot` method, like bar width, color of each bar, and the bar stroke (edgecolor).\n",
    "\n",
    "And now that we have our plot saved as `VOCplot`, we can call all other matplotplib methods on it, too.\n",
    "\n",
    "But what good is a chart that no one else can see? Let's also save it as a PNG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EBQUZnPXT9q39Xn6doX18l7g/BZLgCSGMioODA6mpqURFRemV3blzh5MnT5I/f36DjxIx\n9FiLs2fP8u+//2JtbZ2l2Tut9u3bky9fPlavXs2dO3dYvXo1efPmpUOHDnp1v/rqK3LlysXGjRs5\nceJEun1u27aNQ4cOUbhwYXx9fZXt2kRiyZIl6X4YaWnvQsyIdoYxs4vnP7bMZq0yKs+fPz82Njac\nOXMm07808rbKlStHx44dWb9+PaVKlSI6Otrgo1c+Ng8PDypXrsz169cJDQ3NtL52NtXBwQF49bxJ\nQ7TbtfXSoy039D2ZmJjIvn37UKlU1KxZM9PYtC5cuEChQoUMXlZh6M+kaWMw9D3+6NEj4uLi9JLJ\nd/lZ8imQBE8IYVS0j+6YNWuWzm/lqampjBkzhmfPntGhQwclGUhrwYIFOstYycnJjBkzBniVhL2J\nAgUK0Lp1ax49ekSXLl14/PgxLVq0MLjkVq5cOQIDA0lKSqJDhw4GnwsXHR3Nt99+i0qlYurUqTrX\nXbm4uODn50d8fDxt2rTh3Llzeu1TU1OJjIxM9xloaTVp0gRra2t++eUXNm/ebLDOkSNH3ugu0fdB\nu9yZ3t8LLVy4cIblffv2JSkpid69eytLtmk9evSIAwcOZDmey5cvc+nSJYP9PHnyhNy5c5MrV/Zf\nCaVSqfj+++/JlSsXw4cPZ8WKFQbrnTt3jvbt23Pq1Cng1fMhCxUqRGRkpF6yHx4ezuHDh3We55ie\n9u3bY2Zmxs8//8zZs2d1ymbNmsXNmzf54osv3uhhz+XKleP+/ft63yuhoaHs2LFDr36TJk2wtLRk\nzZo1eu/xtGnTDCbi7/Kz5FOQ/WeeEEK8R3Xq1GHw4MHMmjWLunXr0rJlSwoUKMDOnTuJi4ujRo0a\nStL2OhcXFzQaDa1ataJAgQJs27aNkydPUrt2beUhum/im2++ISwsTHlMRUZLdkFBQTx//pzZs2dT\nr1496tevT/Xq1UlJSeHQoUPExsaSO3dupk+frvdXLODVkpWpqSmLFy/G1dUVd3d3atSoQZ48ebh1\n6xZRUVFcu3aNBg0aZBp3rly5CAsLo3Xr1nTq1AknJyfs7e2xsLDg+vXrxMXFce7cOeVvw34sVapU\noVSpUuzZs4dvv/0Wa2trTE1NadKkCTVq1MDZ2RkLCwvWrFlD7ty5KV26NCqVig4dOlCmTBk6derE\nkSNHWLhwIQ4ODjRs2JAyZcrw4MEDrly5wp49e2jQoEGW75g+evQonTt3platWlSpUoUSJUqQkJDA\nli1bSEhIoF+/fuTNm/cDH5WscXd3JywsjB49etC7d29mzJiBh4cHRYoUUWaw9u/fT548eZRLEfLl\ny8f8+fPp0qULLVu2pEWLFpQrV45jx46xbds2LC0tWbBgQaZjlylThuDgYAYPHoyXlxctW7akWLFi\n7Nu3j9jYWEqVKsWsWbPeaH969eqlPHpH+z1+6NAh9u3bh6+vr94d3hYWFsyePZuuXbvStGlTWrVq\npTyL7+TJk7i5ueklse/ys+RTIAmeECLHSu+PtI8aNQp7e3sWLlzIypUrSUxMpHz58gQGBjJw4ECD\nS60qlYopU6awfv16QkNDuXLlCkWLFqVPnz4MHz5c5+GvWeXo6IidnR3Hjh2jatWqBh98nNaYMWNo\n2bIlixYtIiYmhtjYWFQqFaVLl+Z///sfvXr1SvdvhObKlYuZM2fy9ddfs2TJEmJjYzlw4AAvXryg\naNGi1KxZk9GjR9OmTZssxW5jY0NMTAzz589n8+bNREREkJqaSvHixalWrRoDBgzQuaEjvffibRnq\nz8TEhPDwcMaOHcuWLVuUWZfSpUtTo0YNChYsSFhYGMHBwaxdu5bHjx+jUqlwc3NTHnYcHByMt7c3\nP//8M9HR0cTHx2NpaUnJkiX53//+p5c8Z7RPjo6OBAQEEB0dza5du4iPj6dw4cJUqVKFKVOm6Cyj\nv+m+fog2jRo14tChQyxevJg///yTDRs28PDhQywsLKhSpQpDhgzRe1h2o0aN2Lp1K7NmzWL37t0k\nJCRQrFgxOnXqxJAhQ5QHPmcWl7+/P9bW1oSEhLBx40aePHlCyZIl6dGjB4GBgXrPU8xs/xo2bEhE\nRAQzZsxg7dq1mJqaUrt2bTZs2MDFixcN3hzk6+vL6tWrCQ4OJjIyEnNzc9zc3Pjzzz+ZNWsWe/bs\n0WvzNj9LPhWqhISEnPVH+4QQ4j1r2rQpsbGxxMXF6fzVAyGEyKnkGjwhhCDjmRohhMhpJMETQgje\n/a8kCCHEp0QSPCHEf977vn5MCCGym1yDJ4QQQghhZGQGTwghhBDCyEiCJ4QQQghhZCTBE0KIdLz+\n1P2cJifHn5Njh5wdv8RuHCTBE0IIIYQwMpLgCSGEEEIYGUnwhBBCCCGMjCR4QgghhBBGRhI8IYQQ\nQggjIwmeEEIIIYSRkQRPCCGEEMLISIInhBBCCGFkJMETQgghhDAykuAJIYQQQhgZSfCEEEIIIYyM\nJHhZNHHiRAICApTXf/zxB2q1mlOnTinbvvzyS8LCwgBQq9W4u7vj4eGBp6cnu3fvBmDmzJl06tRJ\naRMfH4+trS1xcXF6Y4aHh1O2bFk0Go3yNX78eKVMrVazdu1anfp+fn4AXL58mcKFC+u0bdWqlV6Z\nh4cH3t7eHDlyRGfsHTt24OPjg4ODA15eXnz++ecsX76cmJgYHB0defr0qVI3IiKCRo0akZqaqtNH\nVFQUXl5eevt1+fJlKlasaPA4P3r0iCFDhuDo6IhGo6F+/frMmjXLYN2MpD12rq6udOnShYSEBKX8\nm2++oVKlSrx8+VKn3evv265du3TKExISKF68OMOGDdMb87fffsPT0xNnZ2fq169Pt27duHbtmtJv\n2mMGYG1tzdWrVwFo2rQpW7Zs0Snv0qULy5cvZ+bMmcp7WLp0aRwcHNBoNHh6enL9+nWaNm2qbNN+\n7d+/Xy++GjVqcODAAZ3+GzRooLy+e/cuxYsXJzExUTm/fvrpJ6U8NTWVmjVr6rx3dnZ2ODs7K+OO\nGDFCb1whhBAfX67sDiCn0Gg0DB06VHkdExNDnTp1iI6Oplq1aiQnJ7N3716Cg4OVOtu2bSNfvnxs\n2rSJrl27cv78eQYOHMgXX3xBREQEHTp0IDAwkK+++gp7e3u9MVUqFQ0aNGDJkiUGy8qUKcOkSZNo\n0aIFpqamqFQqnTqWlpZERUUZ3J+0ZYsXL6Z///5KErpjxw769etHaGgotWvXBuDKlSv8+uuvdOrU\nCW9vb8aMGcP06dO5ffs2EyZM4Pfff9cb/02lpqbSvn177Ozs+Pvvv8mVKxeJiYksXbr0jftKe+xS\nU1Px9/dn+vTpTJo0ifj4eGJiYrC3t2fTpk20aNFCp632ffvzzz/p1q0b58+fV8pWrlxJgwYNWLt2\nLRMmTCB37twAhIaGMn/+fFasWEGFChUAiI6O5t9//6V06dLpxpj2/68fP+22gIAA5ZeLZs2a0b9/\nf7y9vXXqTZs2TWebIR4eHkRHRyvvaVxcHAUKFODRo0cUKFBASd7Nzc0BsLe3JyIigu7duwOvEna1\nWs2TJ090xg4NDaVatWoZji2EEOLjkhm8LHJ2duby5cvcvXsXgNjYWAIDA4mOjgb+/4dl+fLl9drW\nr1+f+/fvc//+fUxNTZk/fz5jxoxhwYIFnD17VidxTCs1NVVvViytWrVqUblyZZYtW6bUfxvu7u6c\nOXNGeT1t2jSGDh2qJAIAZcuWZciQIQCMGTOGXbt2ERUVxaBBg+jfvz/W1tZvNXZau3fv5urVq0yZ\nMoVcuV797mFubs633377xn2lPXYqlQqNRsO5c+eAVzNtPj4++Pn5ER4enm4f7u7u3L9/X3nP4dXM\nYP/+/XFwcGDTpk3K9uDgYKZMmaIkd/AqoXJ0dNSJ6X0w1E9W+tYmeACnTp2iUqVKuLm5sWfPHuBV\nQqrRaIBXx6x8+fLkzZuX06dPA7B8+XI6deqkN9b72i8hhBDvjyR4WZQ3b14cHR2Jiori0aNHPH36\nlM8//5yjR48Cuh+OWtoPvrVr11KqVCkKFSoEQLVq1ejcuTPfffcd8+fPx9TUNN1xd+3apbP09noy\nN2rUKGbMmMHz58/12j548ECnbdol5rQ2bNigM4MYFxenk9wZOhbz5s2jc+fOPHr0iB49eqRb900c\nOXIEBweHDI/H20hMTGTz5s3KPoaHh9OhQwd8fHw4cOAAt27d0qmvPbYbNmygVKlSFC5cGIBjx47x\n8OFDXF1d6dChg7Icf+fOHW7cuJHhMQPw9vbWeT8ePHiQaeyGkqfXZ/pSU1MJCgrS6fvevXt67TQa\nDfv27SM5OZno6Gjc3d1xc3NTkr7o6Gg8PDx0xu3QoQMrVqzgyZMn7Nu3jy+++EJvbD8/P2XcnTt3\nZrpPQgghPjxZon0D2hmQAgUKULduXUxMTKhYsSKnTp0iOjoaX19fnfre3t6YmJhgZWWlM1OUlJTE\n1q1bKVmyJMeOHcPW1jbdMevXr5/hEmX16tVxc3Nj4cKFFClSRKesYMGC6S7RapO/e/fu8fTp0ww/\nmP38/Dh//jx37txRZnOcnZ2xsbGhd+/e6bZ7UyqV6r3OBmmTYwBXV1cGDx7MkSNHePjwIXXr1gWg\nefPmrFixgkGDBintvL29efz4Mbdv3yYyMlJJqJYtW0b79u0B8PHxISAggFu3bmU5IdUu/WqlvZYt\nveVtE5PMfwfL6hJt+fLlKViwIIcPHyY2NpbevXtTrlw55s6dy71797h06RIuLi46bVq2bEn9+vWx\ntramWbNmevsqS7RCCPFpkgTvDWg0GgIDA/nss89wd3cHwM3NjV27drF3716mT5+uU//1D3StmTNn\nUrlyZYKCgvD19cXLywsrK6u3jmvEiBF4e3vrJCmZ0SZ/KSkpDB8+nEmTJikX1Nvb23Pw4EEl8Vy6\ndClPnjzRu5bM1NT0vc621axZk0WLFpGcnJxpv+Hh4SxYsACAAQMG0LZtW706Xl5eetcvhoWFER8f\nr8zmvXjxgvz58+scO+37FhISwpgxY/jjjz948eIFq1atIk+ePCxfvhyAly9fEh4eTkBAACVLluTA\ngQMGbyrJiiJFiujNut27d4+iRYu+VX/p8fDwICoqisOHD1OrVi1MTU159uwZmzdvxtHRETMzM536\nFhYWODk5MW7cODZs2PBOCXj3gZPfNfyP7tmzZ+TNmze7w3hrOTn+nBw75Oz4Jfbs8dPs795rf5Lg\nvQHtdXjr16+nZ8+ewKsEr1evXlhaWlK2bNlM+4iLi2PZsmVER0ejVqvp0aMHgwYNUpKGt1GuXDla\ntGjB/PnzqVWr1hu1NTExYfz48dSuXZvY2Fjc3NwYMmQIAwYMwNbWVrmGLO2F9R9KvXr1KFWqFCNG\njFBuYEhMTCQ0NJT//e9/OnW/+uorvvrqqwz7ez0ZSUxMZPXq1ezevVvnWsk6deqwZ88eZVZPq1+/\nfqxbt46IiAjy5MlDlSpV2Lx5s1K+f/9+evbsSUBAAEOGDGHEiBEsX75c6TsmJkZZ2s+Ml5cXERER\ntG7dGnNzc44ePcqZM2cyXfZNb1/T4+HhwaxZs6hQoYKSRDs7OzN79mzatWtnsM3AgQOpXbs2NjY2\nXL58OUvjGGJZJ+it22YXy+wO4B3l5PhzcuyQs+OX2I2DJHhvwNzcHCcnJ27duqXMuNWqVYtbt27R\nsmVLnbqGltySkpLo06cPkydPRq1WA9C/f3+++OILVq1apTcLpVKpdJYZARwdHZkzZ47eXZdDhw5l\nxYoVOtu0y7Bp+/vrr7/04jM3N2fkyJGMHj2aP//8k4YNGzJ79my+++47bt26RbFixTAzM2POnDlv\ndLxUKhXHjx+nRo0ayrb69esTFBREQkKCzvYqVaqwdu1aVq5cyfjx43F2dlZ+C/vyyy/faFzt2K+/\nBxs3bqRixYp6N8K0a9eO8PBw6tatq9dmwoQJ9OjRgwoVKijLs1p16tQhJSWF2NhY/P39yZMnD126\ndOH58+eYmJhgZ2fHuHHjlHgMxajVuXNnrl69ipeXF6ampuTNm5dffvkFS8us/bgKCgpi4sSJyusR\nI0bQuHFjvXoeHh707dtXJzl2d3cnNDRUuf5OG5s2vqpVq1K1alWDcQshhPg0qRISEuQWOCHEBxcY\nnpzdIQiv3VcuAAAgAElEQVQhxCdrxlfv9wZDuYtWCCGEEMLISIInhBBCCGFkJMETQgghhDAykuAJ\nIYQQQhgZSfCEEEIIIYyMJHhCCCGEEEZGnoMnhPgoEvYHZ3cIbywnPxUfcnb8OTl2yNnxS+zZ5Kv3\n+5cs5Dl4QgiRjrNnz1K5cuXsDuOt5eT4c3LskLPjl9iNgyzRCiGEEEIYGUnwhBBCCCGMjCR4Qggh\nhBBGRhI8IYQQQggjIwmeEEIIIYSRkQRPCCGEEMLISIInhBBCCGFkJMETQgghhDAykuAJIYQQQhgZ\nSfCEEEIIIYyMJHhCCCGEEEZGEjwhhBBCCCOTK7sDEEL8N0wP6JVtY6fkK0jQhKnZNr4QQnxskuAJ\nIT6KiZoK2Tb2yKiL2Ta2EEJkB1miFUIIIYQwMpLgCSGEEEIYGUnwhBBCCCGMjCR4QgghhBBGRhI8\nIT4COzs7nJ2d8fDwwNHRkU6dOvH3339nd1jpUqvVPH36NNN68+fP5+7du8rrKVOmMGrUqA8ZmhBC\niCyQBE+Ij0ClUhEaGkp0dDQHDx6kY8eOtGvXjgMHDmR3aKSkpLx12wULFnDnzh3ltUqleh8hCSGE\neEeS4AmRDZo3b07Xrl0JCQkB4MWLF4waNYqGDRvi4eFBjx49ePLkCQC9evVi8ODBtGjRgtq1a9Oz\nZ08Arl69StWqVXn58qXSb5cuXYiIiABg69atNG7cmPr16+Pt7c0///wDQFRUFG5ubvTp0weNRsOf\nf/6ZYax2dnZMnjwZb29v7O3tWbRoEQAzZszg1q1b+Pn5odFoOH369Ps9SEIIId6aJHhCZBNHR0dO\nnToFwJw5cyhYsCDbt28nOjqa4sWL8/333yt1T548yapVq9i7dy9Hjhxh9+7dlClTBhsbG7Zt2wbA\n/fv3iYmJwdfXl4sXLzJjxgxWrlzJrl27mDNnDv7+/kp/p0+f5ptvviEqKgpvb+8M41SpVDx//pyt\nW7eyYcMGxo0bx9OnTwkMDKR48eKEhoYSFRVF1apV3/9BEkII8VbkQcdCZJPU1FTl/5s3b+bx48dE\nRkYCr2b07OzsgFcJVtOmTTEzMwPA3t6eCxcuUK9ePTp16sTy5cvx8fFh5cqVNGnShLx587J9+3Yu\nXrxIkyZNlDFSUlKU6+UqVqyIk5NTlmNt3bo1AGXLlsXS0pIbN25QqVKlN9rfdr/sfqP679O/z+H0\nwMlv3O7Zs2fkzZv3A0T0ceTk+HNy7JCz4/8vxa7Or2L6xOEfMKLsIwmeENnk0KFDVK9eXXk9c+ZM\nNBqNwbrm5ubK/01NTZVl2WbNmvHdd98RHx/P8uXLCQ4OVuo1bNiQBQsWGOzPwsLijWLNkyeP8n8T\nExOdZeGssmy//o3bvC+WH7ndpyInx5+TY4ecHf9/Kfb4/cGZV8qhZIlWiI8k7Yzdxo0bWbx4MX37\n9gXAx8eHH374gefPnwPw6NEjzpw5k2mf+fLlo0mTJowdO5YnT57g6uoKQIMGDdi+fbuyBAxw8ODB\n97k7ABQoUIAHDx4or9PuoxBCiOwjM3hCfCR+fn6YmZnx9OlTqlWrxqpVq3B0dARg0KBBTJ06lQYN\nGqBSqVCpVAwbNowqVaoA+nenpn3dqVMnfHx8GDlypLLN2tqahQsX0q9fP549e0ZSUhKurq7KeJnd\n7ZrVu2F79OhBnz59yJcvH4sWLVJiF0IIkb1UCQkJ8iu3EOKDCwxPzu4QhBBCR8L+YH6a/V12h/FB\nyBKtEEIIIYSRkQRPCCGEEMLISIInhBBCCGFkJMETQgghhDAykuAJIYQQQhgZeUyKEOKjSMiBDxTN\nyU/0h5wdf06OHXJ2/P+l2NX5jfexTvKYFCGESMfZs2epXLlydofx1nJy/Dk5dsjZ8UvsxkGWaIUQ\nQgghjIwkeEIIIYQQRkYSPCGEEEIIIyMJnhBCCCGEkZEETwghhBDCyEiCJ4QQQghhZCTBE0IIIYQw\nMpLgCSGEEEIYGUnwhBBCCCGMjCR4QgghhBBGRhI8IYQQQggjIwmeEEIIIYSRyZXdAQgh/humB/R6\np/Yp+QoSNGHqe4pGCCGMmyR4QoiPYqKmwju1Hxl18T1FIoQQxk+WaIUQQgghjIwkeEIIIYQQRkYS\nPCGEEEIIIyMJnhBCCCGEkflPJHh2dnZUq1aNlJQUZVt4eDhqtZpFixYpr/38/AC4fPkyFStWNNiX\nWq3m6dOnBsdwdnZGo9EoX1evXtUrc3NzY9WqVTptf/zxR+rWrUvdunXx9PRkwIABPHjwAIBr167h\n5+eHg4MDjo6OtGnThpMnT+q037BhA/Xq1cPZ2ZlatWoxcuRIXrx4YTC218d/8eIFAQEB1K1bF3d3\nd4PxGfI2xygpKYlJkybh5OSEu7s7np6ejBw5kpcvX2Y63uvOnz9Ply5dqFmzJp6ennh4eDB+/Hjl\nPU5NTWXmzJk4OTnh4uKCq6sroaGhWY7f3d0dd3d3nJyc6N69O6dPn1bKp0yZQuXKlXXe64ULFypl\narWaAwcO6NQfNWqUwbGaNm2Kg4MDGo0GV1dXunTpwsOHDwGIioqiRIkSyvvWsmVLLl++rLTt1asX\nNWrU0IkjMjKSXbt24eLiotR78OABhQsX5qefflK2hYSE0KNHD70YtF/79+/XK3NxcWHevHkA9O3b\nl7Fjx+rsi6+vL7/88ovB/RRCCPFx/SfuolWpVJQoUYLt27fzxRdfALB8+XIcHBxQqVTvbYzQ0FCq\nVauWYdnJkydp2LAhDRs2RK1WM3HiRGJjY/n9998pUqQIAL///jvx8fHky5eP1q1b4+/vz9KlSwGI\njIykZcuW7Nu3D0tLS2JiYggKCmLVqlXY2NiQmJhIr169CAwMZO7cuZmOv2DBAhISEoiNjUWlUvH0\n6VNu3br1Xo7J6/r06UNiYiK7d+/GwsKC5ORkwsLCSExMJFeurJ+Kt27dwsfHh3HjxilJ2+PHj5k9\nezaJiYnkzZuX6dOnExUVxfbt2ylYsCDXr1+nbdu25MmTh/bt22c6xrZt28iXLx+pqaksWbKERo0a\nsXv3bsqVK4dKpaJjx46MHz9er51KpaJMmTKMGzeO9evXK9vSo1KpmDZtGt7e3gB07dqVX375hQED\nBgBQrVo1du7cCcDYsWMZOXIky5YtU9oOGjSI7t276/T57NkzLl++zN27dylSpAh79+7F0dGR6Oho\npW50dDTNmzc3GEN68d2+fRsXFxfq16/P5MmT0Wg0NG/enNq1a/PLL79gamrKN998k+mxFUII8eH9\nJ2bwADp27Mjy5csBuHTpEs+ePcPGxobU1NT3NkZW+rKxsSF//vxcvHiRx48fM2/ePEJCQpTkDqB5\n8+aUL1+eVatWYWlpSe/evZUyX19f3N3dlZnHqVOnMmTIEGxsbAAwNzdn1qxZrFmzhmvXrmU4PsCN\nGzcoWrSokoTky5cPa2trAG7evIlGo3nLo6Hr/PnzbNy4kblz52JhYQGAqakpfn5+yuus+umnn6hX\nrx4dO3ZUtuXPn5+RI0eSN29enj9/zuzZs/n+++8pWLAgAKVKlWLChAlMmTLljcZSqVR88803NGzY\nkJ9//lnZntF73aJFC+7fv8+OHTuyNIa2r6SkJJ4+fYparTZYz93dnTNnzhhsm1bevHmpVasWUVFR\nAMTGxvLtt99y7NgxAJKTk9m7d6/Oe5uVc9fKyopKlSpx9uxZPvvsM+bMmUOfPn04d+4cM2fOJCQk\nJEv7K4QQ4sP7zyR4Hh4enDhxgoSEBJYvX06HDh3ea/+pqan4+fkpS1wNGjTQKwfYs2cPz549w9ra\nmtOnT2NmZpbuUuHx48dxcnLS2+7k5KR8WJ84cUKvjqWlJeXLl+fEiRMZjg/QpUsXIiMjcXNzY/Dg\nwWzcuFFpU6JECSVJeFdxcXFYW1srCde79lW7du10yy9cuEDu3LmpVKmSznYnJycuXbpkcPk4M7Vr\n1+bUqVPAq2MZERGhs6T5559/KnVVKhWjR49WZvgySp5SU1MJCgpCo9FQpUoV4uPjDZ6bKSkpbNq0\nCXt7e522s2fP1olDe15oNBqio6MBiImJwdPTk4oVK3Lq1Cni4uL47LPPKFeunF4M2q979+7pjANw\n9uxZzpw5Q40aNQCoX78+7u7uNGjQgOHDh1OqVKk3Pq5CCCE+jP/EEi28+tBt2bIlq1evZu3atWzd\nupXDhw9/lCVabfKXmprKhQsXWLx4MZaWllnq11BykJqaqsSdlZmXjMavXr06hw8fJjY2lr179xIU\nFMT27duZNWtWluLLLmn3e/bs2axevZr4+HgWL16c6Yzg28zapr1+E0h3iRZenQve3t58//33rFu3\nLstLtCkpKQwaNIgxY8YoM42nT59Go9Fw8+ZN8ubNy19//aXT1tASLbz6hWbIkCE8fvyYJ0+eYGVl\nhbu7O9HR0Tx79kxn9i6jJVpt8jd27FjOnDnD2LFjqVy5slLer18/1qxZw1dffZXuPgohhPj4/lMJ\nXseOHfn8889xd3dPdxnsQ42tTf4iIyMZN24cjRo1omrVqiQmJnL+/HmDs3i2trY6y4Ja//zzjzKL\nYmtry/79+7G1tVXK4+PjuXTpkrJsa2h8b29v8ubNC7xa1vXy8sLLywtvb29atWr13hM8e3t7Lly4\nQEJCQqbJ7Y4dOxgzZgwA7du3p1+/fnp9HTp0SHk9cOBABg4ciJeXF0lJSVSsWJGkpCTOnj2rk4zs\n37+f8uXLY2Fhwd27d98o/kOHDlG9enXg1fHMbFYOYMyYMfTr1w9fX98sjWFiYkKzZs0YPXq0sq1q\n1ars3LmTpKQkunbtSkhIiE55epydnbly5Qrr169Xbrhwc3MjJCSE58+fZzmmtMnfvn378PPzo337\n9lhZWSnlJiZZWwho98vuLNVLz7/P4fTAye/Ux5t69uyZ8n2SE+Xk+HNy7JCz4/9UYlfnVzF94vDs\nDiPH+s8keADly5dn1KhROst7bzObk16brPTl6+vL2rVrmTt3LkOHDqV3794MGDCAJUuWUKRIEVJT\nU9m4cSO2tra0adOGmTNnMm/ePPr06QO8uskiNjaW77//HoChQ4fSo0cPXFxcqF69Os+fP2fw4MG0\natWKMmXKpDt+SEgIQ4cOZc+ePVSuXFm5BvDw4cPK0t2NGzdo2bIlf//99zsfo4oVK+Lj48OgQYMI\nCQkhf/78JCcnEx4eTps2bXRm3Ro0aKC3xJ1W9+7d8fT05Ndff+XLL78EXl1XlpiYCECePHkYMGAA\ngwYNIiwsDEtLS65du8aYMWMYNmzYG8WfkpLCsmXL2LFjB7t37za4b+ntt6urK9bW1qxcuZIWLVpk\nqU1UVJTe0jJA7ty5mTVrFi4uLnTp0oXy5ctnGEuePHlwdHRk1qxZDB/+6gekg4MDhw4d4sGDB8yY\nMSPdGNKLz8XFhfbt2zNhwgR++OGHdOunx7L9+jduo9P+nVrnnDHfp5wcf06OHXJ2/J9K7PH7g7M7\nhBztP5XgAcqjULS0y2cqlUpnKS0hIUGZJQOoUqUKa9euBaBOnTpKXQsLCyUB8vPzw9zcXGkTEhKC\ng4ODXgxjxoyhYcOGdOvWjdGjRzNv3jyaNWsGvPowdXNzQ6PRkDt3btasWcOIESNYuHAhJiYmVKhQ\ngbVr1yqzYB4eHkydOpWePXvy/PlzXrx4QdOmTTOc5Uk7/pUrVwgKCiIpKQkTExOKFSumPPLj1q1b\nGd7d+qbH6McffyQ4OJj69etjZmZGSkoK3t7eOscsK4oXL86mTZsYN24ckyZNonDhwpiZmdG8eXPl\nGrWhQ4diampKw4YNlX3o1auXkhBmFr92uTIxMREHBwe2bNlC2bJlgVfnSkREBLt27VLaNmnShOHD\nh+udR6NHj8bT0zPDZdqgoCAmTpzIy5cvKVOmjDJ7+npfRYsWpWfPnowfP57FixcDr5an0z7+pVu3\nbvj7+wOvrsObNm0a7u7uAOTKlYuKFSty4cIFveRfG4PWiBEjaNy4sRKHVkBAAE5OTpw6dUq5HOF9\nXeYghBDi/VElJCS8v9tIhVGZN28exYoVo127dtkdijACgeHJ2R2CECIHSdgfzE+zv3ujNq9fmvNf\n9p+bwRNZp10WFkIIIUTO8p95TIoQQgghxH+FJHhCCCGEEEZGEjwhhBBCCCMjCZ4QQgghhJGRBE8I\nIYQQwsjIXbRCiI8iIQc+tPRTeaL/28rJ8efk2CFnx/+pxK7OL8/YfBfyHDwhhEhHTn+mVk6OPyfH\nDjk7fondOMgSrRBCCCGEkZEETwghhBDCyEiCJ4QQQghhZCTBE0IIIYQwMpLgCSGEEEIYGUnwhBBC\nCCGMjCR4QgghhBBGRhI8IYQQQggjIwmeEEIIIYSRkQRPCCGEEMLISIInhBBCCGFkJMETQgghhDAy\nubI7ACHEf8P0gF5621LyFSRowtRsiEYIIYybJHhCiI9ioqaC3raRURezIRIhhDB+skQrhBBCCGFk\nJMETQgghhDAykuAJIYQQQhgZSfCEEEIIIYxMpgleUlISkyZNwsnJCXd3dzw9PRk5ciQvX74E4MSJ\nE7Rp0wZHR0ccHBzw8/Pj+vXrSvtevXqxaNEivX4TExMZMWIEtWrVwtnZGU9PTzZu3KiUR0VFUaJE\nCTQaDW5ubrRs2ZLLly/r9LFt2zbUajUbNmzQ2d6rVy9q1KiBp6cntWvXxsfHh19//VWnzrVr1/Dz\n88PBwQFHR0fatGnDyZMn0z0OarWap0+fAtC0aVMqV67MkydPlPKmTZuyZcsWZs6ciUajQaPRULp0\naRwcHNBoNHh6enL9+nWaNm2qbNN+7d+/X+lDW+bi4sK8efN0Ypg0aRJ169bFw8MDV1dX5s2bx4kT\nJ5R+bG1tKVeunPL6559/BuDnn39GrVYTFxcHQGBgoFKnaNGiODs7KzGmpKRgZ2enbNN+Xb161eBx\nOXToEG3atKFmzZrUr1+fevXqERISolMnISGB4sWLM2zYML3t3bp1w83NDTc3NzQaDX/99ZfBcd71\nPMzMb7/9hqenJ87OztSvX59u3bpx7do1QPe917K2tlaOifZ8S3u8IiMjiYiIoFGjRqSmpirtpk2b\nRteuXQEyPM52dna4ubnptLWzs+PUqVPKmMWLF1di1G7Tfq+Fh4dTtmxZnb7Hjx9vcN/XrVuHp6cn\nGo0GZ2dnvv32WwAaNmyIRqPB1dWVwoULK/307duXK1euoFarCQgIUPq5fPkyFStWzPIxF0II8eFk\nehdtnz59SExMZPfu3VhYWJCcnExYWBiJiYk8fvyYli1bMn36dHx9fQGYP38+rVu3JiYmhly5cqFS\nqVCpVHr9BgQE8OzZM/bt24eZmRknT56kbdu2qNVq3NzcAKhWrRo7d+4EYOzYsYwcOZJly5YpfYSF\nhdGiRQvCwsJo1qyZsl2lUjFo0CC6d+8OwNGjR+natSt3796lT58+JCUl0bp1a/z9/Vm6dCkAkZGR\ntGzZkn379mFpaZnhMVGpVOTLl48ffviBoKAgZZtKpSIgIED50GvWrBn9+/fH29tbp+20adN0thkq\nu337Ni4uLtSrVw9bW1vWrVtHdHQ0u3fvxszMjKSkJC5cuEDVqlWJiooCYPny5WzdupUlS5bo9Jv2\nOE2bNo0ZM2YoZfb29oSGhlKtWjWdOF7fZsjx48dp164dCxYs4PPPPwfg7t27zJ8/X6feypUradCg\nAWvXrmXChAnkzp0bgIkTJ1K6dGklEU1ISODx48cGx3rX8zAjoaGhzJ8/nxUrVlChwqs7PaOjo/n3\n338pXbq0wTZpz+nXz7e01q9fzw8//EC/fv04fvw4oaGhREdHK+3SO84qlYonT54QERFBx44d9cYE\nKFasGFOmTFF+EXj9e61BgwZ658Lrbt26RWBgIH/99RclS5YEUH4R2L59OwBXrlzBy8tLOc/gVTKX\nP39+Nm3aRL9+/ShfvnyG4wghhPi4MpzBO3/+PBs3bmTu3LlYWFgAYGpqip+fHxYWFvzf//0fnp6e\nyocqQO/evSlQoACrV69WtqWdhYBXHxjr1q1j5syZmJmZAWBjY0NAQADBwcEGY3F3d+fMmTPK6/v3\n7xMTE8PcuXM5cOAA//77r07912c+pk6dypw5cwBYtWoVlpaW9O7dW6nj6+uLu7u7wdlGQwYNGsTP\nP//M/fv3M6z3+r6nt+11VlZWVKpUiXPnzgFw48YNChUqpByv3LlzU7VqVb1+X+/7xIkTPHz4kGnT\nprF27VqSkpIyHTurMc6ZMwc/Pz8luQMoUqQIo0eP1qkXHh5O//79cXBwYNOmTcr2GzduYGVlpby2\ntLQ0mFC9r/MwPcHBwUyZMkVJ7gA8PDxwdHRUXmd2PNIrnzNnDgsWLODEiRP06dOH6dOn6/wCkVG/\nQUFBBAcHK7OUaalUKrp168auXbs4ffr0G8WU1u3bt8mdOzdqtVrZZm9vn6V+zMzM6Nu3LxMnTsx0\nHCGEEB9XhgleXFwc1tbWFCxY0GD5iRMncHJy0tvu5OTEsWPH0u33xIkTVKhQQW+mrHbt2gbbpaSk\nsGnTJp0Pnl9//RUfHx8KFixIixYtWLFiRUa7Qu3atblz5w53797l+PHjbxV3WiVKlKBDhw46s2GG\nvD7rkpqaSlBQkM7S2b1793TKAc6ePcuZM2eoUaMGAG3atOHMmTM4OjrSp08ffvvtN5KTkzONc9my\nZXTo0AErKyscHBz0lrMNSU1Nxc/PT4mvQYMGBuvFxcVRu3btDPs6duwYDx8+xNXVlQ4dOhAWFqaU\n9ejRg2nTptGwYUOGDx+e7vLshzoPAe7cucONGzcy3Q9vb2+d9+zBgwdKWWpqKrNnz9YpP3r0KABF\nixZl4sSJNG7cGBsbG3x8fHTaZXSca9WqhYODAz/99JPBmPLly8egQYOYMGGCwfJdu3bpxJR29lvL\n3t4eR0dHbG1t8fPz48cffyQ+Pj7DY5FW9+7d2bdvn7K/QgghPg3v9KBjQzNG2u2GlmXTlmfF6dOn\n0Wg03Lx5k7x58+okAOHh4Uyd+uoJ+F9++SV9+/ZlwIABWR7zbWfWtLTLci4uLvTp0+eN2qW3RKtN\n/saOHcuZM2cYO3YslStXBl7N6O3du5e///6bvXv3MnPmTH777TdWrVqV7lhJSUmsXr2abdu2Aa+O\nU1hYGK1atco0xqws0b4uKCiI2NhY7t69y/bt2ylZsiTLli2jffv2APj4+BAQEMDNmzcpUaIE9erV\n49ixY0RFRbF37178/f3p378/AwcOfKNx3/Y8fBPbtm0jX758yuu015pltEQL0KpVK0aNGkXfvn11\ntmd2nFUqFSNHjqR58+Z07tzZYLm/vz/z5s3jwIEDeuX169dXLkFIj0qlIjw8nJMnTxITE8PGjRsJ\nCQkhNjY200sVAMzNzRkyZAgTJkzI9Jeddr/s1tv273M4PXBypuNkl2fPnpE3b97sDuOt5eT4P3Ts\n6vwqpk8c/sH6FyK7ZZjg2dvbc+HCBRISEgz+sLe1teWff/7R237gwAH+97//Ka9f/5CtXr06Fy9e\n1Ov3n3/+wdbWVnldtWpVdu7cSVJSEl27diUkJITRo0dz+PBhTp8+rbPEevv2bfbt24eLi4vBMQ8e\nPEixYsUoUqQItra2ynVfab0+fmbUajXffvstkye/+oB6kwTRkLTJ3759+/Dz86N9+/bKMqapqSl1\n69albt26fP3111SpUiXd9wZg06ZNPHz4kObNmwOvZkLv3LnD9evXKVWq1DvFCq/Oj4MHD9KkSRMA\nZXm9YsWKJCcn8+LFC1atWkWePHlYvnw5AC9fvmT58uXKdYr58+fHx8cHHx8fHBwcmDFjhl6C977O\nQ0OKFi1KyZIlOXDgAF5eXm9+ELLIxMQEU1PTN25XqVIlvvjiC3744QeD5bly5WL48OGMGzeO0qVL\nv/U5aGNjg42NDd27d8fV1ZXo6Gid61oz8tVXX/HDDz8QGxubYT3L9uv1t71VtB/Ppx5fZnJy/B86\n9vj9hi8HEsJYZLhEW7FiRXx8fBg0aJBy8XtycjKhoaE8efKEb7/9lqioKCIjI5U28+bN49GjR7Rt\n21bZ9vqHTrly5fD19WXw4MEkJiYCr5bZZs2apdy0kFbu3LmZNWsWS5Ys4dKlS4SFhTFw4EDi4uKU\nr2HDhinLf6/P6Bw7dozvvvtOmeFr06YNCQkJOnepRkZGEhsbm2lC8Po+9e7dm507d3Lp0qUstTN0\nPAyVubi40L59e2X57fDhw1y5ckWpd/jwYdRqdYazLOHh4UyfPl05RseOHaNTp05KsvW2MWr179+f\nJUuWKBfjw6u7o7VLx5s2baJKlSocP35ciWH16tXK+Lt27eLRo0fKeEeOHDF4sf77Og/TM2TIEEaM\nGKHzHsbExHDw4MFM22q9bWKVlXbDhg3jp59+0rsBRdu2Xbt23Lt3j5iYmDeesbx58yZ///238vr6\n9evcvXuXcuXKZbkPU1NTRowYofyiI4QQIvtlukT7448/EhwcTP369TEzMyMlJQVvb2/Mzc2xsLBg\n7dq1jBo1irFjx5Kamoq9vT2rV6/Wma2YNGkSs2fPVl7PmTOHmTNnMn78eFxcXDAzM8Pc3JypU6cq\nd9C+fkdg0aJF6dmzJ+PGjWP37t1s2bJFJ842bdqg0WgIDg5GpVIxe/ZsQkNDefbsGUWLFmXw4MF8\n+eWXwKuEcc2aNYwYMYKFCxdiYmJChQoVWLt2bboJ0+sfnNrX2uuggoKCsvzhGhQUpHNh+ogRI2jc\nuLHeOAEBATg5OXHq1Cnu379PYGAgjx49wszMDAsLC8LDw/Vi0ra/efMmsbGxetdvtWvXjr59+zJk\nyJAMY/Tz88Pc3Fx5HRISgoODg04dW1tbfv31VyZNmsTgwYMpUqQIZmZmBAYGUrx4ccLDw5XlWa06\ndeqQkpJCTEyMknhrVaxYkenTpxuM532ch+nx9/cnT548dOnShefPn2NiYoKdnR3jxo0D9N97Q7Tn\nm/NZAiEAACAASURBVFa3bt3w9/fPtF1WjnPJkiXp0KGD3mNztHGpVCpGjx5Nhw4ddMq01+BpOTo6\nKjcaab18+ZKpU6dy9epV8uTJQ0pKCqNGjcLOzs7gWOlt8/X1Zc6cOXqPkxFCCJE9VAkJCe+2riiE\nEFkQGJ75TUFCfCwJ+4P5afZ3mVd8S2fPnlWuoc5pJHbjIH/JQgghhBDCyEiCJ4QQQghhZCTBE0II\nIYQwMpLgCSGEEEIYGUnwhBBCCCGMzDv9JQshhMiqhBz4YNmc/JcgIGfH/zH+koUQxkwSPCHER/Eh\nH0nxoeT0Ry7k5PhzcuxCfApkiVYIIYQQwshIgieEEEIIYWQkwRNCCCGEMDKS4AkhhBBCGBlJ8IQQ\nQgghjIwkeEIIIYQQRkYSPCGEEEIIIyMJnhBCCCGEkZEETwghhBDCyEiCJ4QQQghhZCTBE0IIIYQw\nMpLgCSGEEEIYGUnwhBBCCCGMjCR4QgghhBBGRhI8IYQQQggjIwmeEEIIIYSRkQRPCCGEEMLISIIn\nhBBCCGFk3muCN3HiRAICApTXf/zxB2q1mlOnTinbvvzyS8LCwgBQq9W4u7vj4eGBp6cnu3fvBmDm\nzJl06tRJaRMfH4+trS1xcXF6Y4aHh1O2bFk0Go3yNX78eKVMrVazdu1anfp+fn4AXL58mcKFC+u0\nbdWqlV6Zh4cH3t7eHDlyRGfsHTt24OPjg4ODA15eXnz++ecsX76cmJgYHB0defr0qVI3IiKCRo0a\nkZqa+kbHtGnTpjg4OKDRaHBxcWHevHlKWVRUFF5eXjr1T5w4gb29vfJarVbrxKFlZ2envC9Hjx6l\nadOmaDQaXF1dadSoEXfu3FHqLl26lLp16+Li4oKTkxOzZs3S2Q+1Wk27du10+k9v3Bo1anDgwAHl\ndZcuXWjQoMH/Y+/Ow6Kq/geOv0dUUimZtNwyVywUEVzQgGERo9DAHXHFyvLrmgiIC4o7mxmlmRmp\nISgl5pJSZiqKkGapoWnuS2maGymLhDC/P3jmfhlmgMGvK7/P63l8dO4599zPOffifLjn3Bnl9bVr\n16hfvz55eXkAHD9+HLVazZIlSwCIj49XzlWzZs1o06aN8vqXX35h1KhRets0Gg2bNm0C0CtzcHAg\nLCystGEnPDwctVrN999/r2zLysqiUaNGBmNeMsaSbRTvb3h4ONOnT9er9/nnn6NWqw2u79u3bxMS\nEkL79u1xdHTEycmJUaNGcenSJaUtKysrvb4uW7asQvHrfgaLt3H37l2lzNh5zc7OZvDgwUr94m30\n69ev1DEVQgjx8FS9n41pNBomTZqkvE5LS6NTp07s2bOHl19+mYKCAvbu3UtkZKRSZ9u2bdSsWZPk\n5GTeeustTp8+zYQJE3j11VdJTEzEz8+PoKAgBg8erJe46KhUKrp27crKlSuNljVu3Jh58+bh4+OD\nmZkZKpVKr46lpSWpqalG+1O8bPny5YwfP15JQnfs2MG4ceOIi4ujQ4cOAFy4cIEvv/ySQYMG4enp\nSVhYGNHR0Vy5coU5c+bwzTffGBy/PCqViqioKDw9Pbly5QqdO3fG1dUVGxubCrVjrF2dd955h9mz\nZ+Pp6QnA2bNnqVmzJlCUmC5dupSkpCQaNWpEZmYmgwcPprCwkKCgIKWNkydPkp6ejqOjY5nHdXZ2\nZs+ePcqYZWRk8PTTT3P79m2efvppJTk2NzcHihI6b29vEhISGD16NEOGDGHIkCEAjB49mvbt2zNi\nxAil/c8//5yAgAC9bcX7rCvLysrCxcWFLl264OXlZbRuu3btWLNmjTIuGzZswMrKyuAcloyxeBuN\nGzdm1qxZSpJp7PzHx8fj4+NDfHw8UVFRAGi1Wnx9fbGxsWHv3r1Ur16dwsJC1q5dy4ULF2jYsCEq\nlYqBAwcqv9Dca/y6n0FjjJ1XlUpFQkKC8lqtVpfZhhBCiIfvvt7Bc3Bw4Pz581y7dg2A9PR0goKC\n2LNnD/DfN/OmTZsa7Ovm5saNGze4ceMGZmZmLFmyhLCwMJYuXcrJkyf1EsfitFptmXfF7O3tsbKy\nYtWqVUr9e+Hk5MSJEyeU11FRUUyaNElJVABefPFFgoODAQgLCyMlJYXU1FQCAgIYP348zZs3v6dj\n69SrV4+WLVty6tSp/6mdki5dukT9+vWV182aNaNWrVpA0Z2gefPm0ahRI6Ao6f3ggw9YuHAh+fn5\nyj6TJ09m1qxZ5R5Ll+AB/P7777Rs2RJHR0d+/PFHAPbs2YNGowHg7t27JCUlMX/+fLRaLQcPHjRo\nz9j5LOsc68osLCyws7Pj5MmTZcb622+/kZmZCRQlu4MGDdJrv7wYfXx8uHHjBjt27DB6jKNHj3Lr\n1i2ioqJYv369Mqa7du3ijz/+ICIigurVqwNQpUoVBgwYQJcuXUzqqynxl9eGqedVCCHE4+W+Jng1\natSgffv2pKamcvv2bXJycujWrRuHDx8G9N+8dXRvLuvXr6dRo0Y8++yzALz88ssMHTqUqVOnsmTJ\nEszMzEo9bkpKit4UU8lkbvr06SxYsIA7d+4Y7PvPP//o7Vt8irm4zZs3691BzMjI0EvujI3Fxx9/\nzNChQ7l9+zYjR44stW55dP04efIkJ06coE2bNvfcljFBQUF0796dPn36EB4eriQ9t2/f5sKFC3Ts\n2FGvfqtWrahatSqnT59Wtnl7e3P37l2Sk5PLPJZGo2Hfvn0UFBSwZ88enJyccHR0VJK+tLQ0nJ2d\nAdi6dSutWrXihRde0JvaL4tWqyUmJkbvnB45csSg3tWrV/npp59o27ZtqW2pVCp69+7N119/zblz\n58jJyaF169Z6dcqLUaVSMWPGDOUuW8lkatWqVfj5+VGvXj3s7OzYvHkzAL/++it2dnZlXvdarZbE\nxES9vv7www8Vih/A09NT2b/40ggw/bwKIYR4vNzXKVr47x2ap59+mldeeYUqVarQokULfv/9d/bs\n2UPPnj316nt6elKlShXq1aunN+2Tn5/P999/T8OGDTly5EiZU5Jubm588cUXpZa3bt0aR0dHli1b\nRt26dfXKateuXeoUrS75u379Ojk5OezcubPUY/j7+3P69GmuXr3K8ePHgaI7mtbW1nrTdhWl1WoJ\nCQlh5syZnDhxgpkzZ2JlZQUYn+4ra3tpxo8fj6+vL7t37yYlJQU3NzfWrl1bbvJT8vWMGTOYMmWK\n0SlPnaZNm1K7dm0OHTpEeno6o0ePpkmTJnz00Udcv36ds2fP0rlzZ6Bo6nLAgAEA9O/fH2dnZ+bP\nn69M35YWV2lTtLrkb8WKFZw6dQp/f3+D9XQlDRw4kHfeeYcrV64wcOBAg3JjMYaHhyt33VQqFZ6e\nnnzwwQds2LBBb9zy8/NZt24d27ZtA/67PlW3DrR4MpiSksL06dPJysrirbfeYty4cWVO0ZoaP5Q9\nRWvqeTXFiAnz/6f9H4Xc3Fxq1KjxqMO4Z09y/KbGrrZQET13ykOISIgny31P8DQaDUFBQTzzzDM4\nOTkB4OjoSEpKCnv37iU6OlqvfmlvLu+//z5WVlaEhITQs2dP3N3dqVev3j3HNW3aNDw9PQkICDB5\nH13yV1hYyJQpU5g3bx6xsbEA2NracuDAASXx/OKLL8jOzuaFF17Qa8PMzKzMuzBDhgzh/PnzqFQq\nkpOTsbCw0CsvvgZv3759+Pv74+vrS7169ahbty43btzQq3/9+nWee+45k/uoU79+fXx9ffH19aVG\njRps3LgRR0dHmjRpwv79+/Hw8FDqHj9+nPz8fIMpZ1dXV55//nkSExPLPJazszOpqakcOnQIe3t7\nzMzMyM3N5dtvv6V9+/ZUr16dv//+m507d3L48GEiIiIAuHPnDps2bTJY+G+q4snfqVOn8Pb2Zvjw\n4aXeEVWpVDRt2hRzc3NWrVpFenq6cjcaKDXGjRs3KjHqkrSwsDDGjRun9wtOcnIyt27dwtvbG4DC\nwkKuXr3KxYsXadeuHbGxsRQUFGBmZoabmxupqalMnz6d7OxspY2yplfLi99Upp7X8lh2Cvmf9n8U\nLB91AP+jJzl+U2O/uT+y/EpC/D903z8mRbcOb9OmTcpUm6OjI5999hmWlpa8+OKL5baRkZHBqlWr\nWLBgAa1atWLkyJEVSsyMadKkCT4+PgZPOpqiSpUqzJ49m71795Keng5AcHAwUVFRHDhwQKlX/I3X\nVPHx8aSmprJ7926D5E5H9ybeuXNnfH19mTNnDgAtWrQAUNZ3FRQU8MUXX+g9lVp8/9Js2bKFwsJC\noChBOX78uLJOMiQkhOnTp3Px4kUAMjMzmThxIgEBAcpdquJmzpypJDulcXZ2ZtWqVTRr1kxJfh0c\nHIiJicHFxQUoWi/Ws2dPjhw5QkZGBhkZGSxatMjkadryylq2bElgYCBTp04ttV7x5GzmzJlYWuq/\n5ZQXY/E4unTpQvPmzVm7dq1yFy8hIYHo6Ghl3yNHjjBo0CBWr16Nm5sbjRo1YsqUKcoTxQA5OTnK\n/uX1s7z4TRkvHVPOqxBCiMfHfU/wzM3N6dixIyqVSrnjZm9vz+XLl5WET8fYVGJ+fj5jxoxh/vz5\nqNVqoGgK8cqVKyQlJRnUV6lUBmvw3nvvPaWs+DEmTZrEjRs39LaVXIOnSzBKxmdubk5oaCgzZswA\nwMPDg5iYGKZOnYqdnR2enp689dZbfPjhhxUes/IUjyMwMJCtW7fy+++/U61aNVatWsUHH3ygxP7s\ns88arCPs1KkTbdq0oU2bNjg4OBi0v3HjRjp37oyzszNubm60bduWd999F/jvFF/fvn3p3LkzHh4e\nuLu76z1BWzw+Ozs77OzsypwmdnZ25syZM8odXih6iOXMmTPKNbJ69Wp8fX319vPy8uLgwYP88ccf\nRo+tU3INXvEnrIvXf/PNN7l06ZLeurXi9XR1O3XqpBeLbntpMR46dIgLFy4YXH8zZszgzz//BODy\n5cukpaUZLFno378/a9asAWDt2rVAUXLo5OTE66+/zr///qtMCatUKoM1eOHh4WXGXzIm0F+Dp9Fo\nuHLlisFYlXVeK7okQAghxIOnyszMvLfHSoUQogKCEgoedQiiEsrcH0lsjPE78Y/SyZMnlfXSTxqJ\nvXKQb7IQQgghhKhkJMETQgghhKhkJMETQgghhKhkJMETQgghhKhkJMETQgghhKhkJMETQgghhKhk\n7vs3WQghhDGZT+A3DjzJX/UFT3b8FfmqMiGEIUnwhBAPxeP4WWXledI/U+tJjv9Jjl2Ix4FM0Qoh\nhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBC\nVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDKS4AkhhBBCVDJVH3UAQoj/H6ID\nR5lct7BmbULmRDzAaIQQonKTBE8I8VDM1TQzuW5o6tkHGIkQQlR+MkUrhBBCCFHJSIInhBBCCFHJ\nSIInhBBCCFHJSIInhBBCCFHJPPQEr23btjg4OKDRaJQ/f/zxh1Lm6OiIVqvVq3/s2DGCg4OV+s89\n95zShouLC4WFheW2qytzdHQkKSlJaT81NZUGDRooZb179+bChQsAjBo1ijZt2qDRaHBwcCAsLEyv\nL2q1mpycHAB2795Nt27d0Gg0dO7cGR8fH6Vejx49sLOz04tt//79Rsfn9OnTDBs2jHbt2uHi4oKz\nszOzZ8+msLBQqVNQUIC1tTWDBg3S2/fff/8lMDCQV155BScnJ4O+Flc8JgcHB5YuXQrA+fPnqVOn\nDhqNBmdnZzw9Pfn111/19t28eTOurq44ODhgb29PaGgo//77r1Ken5/PvHnz6NixI05OTri4uBAa\nGsrdu3eNxlKa1NRU1Go1M2bMMIi9+NiXNb7llW3dulUZ01GjRtG/f39yc3MJDw/HyspKb79ly5YB\n6JV17tyZMWPG6PW/pIMHD9K3b1/atWuHm5sbrq6uLFq0SK9OZmYm9evXZ/LkyQbb3377bRwdHXF0\ndESj0bB7926jx9Fd587Ozjg6OvL1118r4+ju7l5qfKUdOyEhAbVazfr16/W2+fv7c/ToUWVcbGxs\naNKkifL6888/L/VYQgghHo6H/hStSqUiLi6Ol19+2WhZdnY2iYmJDBw4UNmmUqmIjo5W6tna2hq0\nUV67urJjx47h4eGBh4cHarUagJdffpmdO3cCMG3aNKZNm8aqVatQqVQEBAQwYsQIsrKycHFxoUuX\nLnh5eem1f/fuXYYNG0ZycjKtW7cG4PDhw3rHj4qKwtPTs8yxuXz5Ml5eXsyaNYu4uDgAsrKyiImJ\nIS8vjxo1agDwww8/0KJFCw4cOMDVq1d57rnnAFi6dCmZmZmkp6ejUqnIycnh8uXLRo9VPKaLFy/y\nyiuvoNFosLCwwNLSktTUVACWL1/O+PHj2bVrFwBpaWmEhISQlJSEtbU1eXl5jBo1iqCgID766CMA\nxowZQ15eHrt27aJWrVoUFBQQHx9PXl4eVauafsmpVCqsrKxITk5m5syZVKlShXPnzpGbm4tKpTJp\nfMsrU6lU5OXl8fbbb1OtWjXWrFlD1apVUalUDBw4kNmzZxvdT1eWn5+Pj48PK1asYOTIkQZ1f/vt\nN/r378/SpUvp1q0bANeuXWPJkiV69dauXUvXrl1Zv349c+bMoVq1agDMnTuXF154QUmaMjMzycrK\nKnW8dNd5RkYGr732Gm5ubqWMbvnHVqlUNG7cmHnz5uHj44OZmZky7q1bt1aukdWrV/P999+zcuXK\nco8lhBDi4XgkU7TF79CVFBISQmRkZIXv9pTXro61tTUWFhacPWv8YxhcXV05deqUQZsWFhbY2dlx\n4sQJg32ysrLIyclREi0ouptS0dhiY2NxdXVVklvdcUNDQ5XkDiA+Ph5/f3+8vb1JTExUtl+6dInn\nnntOeROuWbMmzZs3L/e4jRo1wsrKSq/fOk5OTnp9joiIIDg4GGtrawDMzc1ZuHAhX3/9NX/++Sen\nT59my5YtfPTRR9SqVQsAMzMz/P39ldem0mq11KpVCwcHB7Zv3w4UJRN+fn4G41nW+JZVlp2djZ+f\nH88++yzLly/XS0BNabNatWp07tzZ6HUB8OGHH+Lv768kdwB169Y1uCuZkJDA+PHjsbOzIzk5Wdl+\n6dIl6tWrp7y2tLTkhRdeKDUuHVtbWywsLJS70WUp7dgA9vb2WFlZsWrVKsD4mGi1WpOubyGEEA/P\nQ0/wtFot/v7+ynRO165d9crt7e2xs7MjNjb2vrarewP68ccfyc3NNZr4FBYWsmnTJmxtbQ3Krl69\nyk8//WS0zNLSEn9/fzp06ICfnx8xMTFcvHhR79ghISF6033Xr183aCcjI4MOHTqU2c/r16+TlpaG\nt7c3fn5+JCQkKGXDhg1j48aNODo6MnHiRLZs2VJmW7ox+f333zl58iQ2NjYGdTZv3qzX56NHj9Kx\nY0eD/jdt2pTffvuNjIwMmjdvTu3atcs8dkUMHDiQNWvWALB+/Xr69+9v0I/Sxre8sqCgIOrXr89H\nH32kd1dQq9WSmJiot98PP/xgENvt27fZtWuX0esCTDunR44c4datW3Tp0gU/Pz/i4+OVspEjRxIV\nFYWHhwdTpkwpdXq2eNxQtGQgLy+v3AS/rGPr2po+fToLFizgzp07ZbYlhBDi8fFYTdHqykNDQ/H2\n9mbo0KH3pV1d8qfVajlz5gzLly/H0tJSKT9+/DgajQatVouNjQ3z589X9ouJiWHFihWcOnUKf3//\nUtcyRUdHM2bMGHbv3s0PP/zAwoULSUlJoXnz5iZP0eqOqRMTE8O6deu4efMmy5cvx8HBgcTERF5/\n/XWeeuopOnToQGFhIfv376dTp060bt2aQ4cOkZ6ezt69ewkJCWH79u0sXLjQ6HFCQkKYO3cuTz31\nFDExMbRo0YLz58/zzz//KIlQTk6OMn1dMj5j56B4knS/aDQagoKC+Oabb2jdurUytV78uPc6Revh\n4UFKSgrHjx/npZde0isrbYpWl/zt3LmTM2fO4Orqir+/v0l9CQkJIT09nWvXrrF9+3YaNmzIqlWr\n8PX1BcDLy4vAwED++usvGjRogKurK0eOHCE1NZW9e/cyfPhwxo8fz4QJE4zG5e/vj7m5OU8//TSr\nVq3imWeeKTOeso6t07p1axwdHVm2bBl169Y1qZ/G9F+xy+S6f9+B4xPm3/Ox7pfc3Fy9u+dPmic5\nflNiV1uoiJ475SFFJMST5bH8JouWLVvy6quvsnjx4vvSXvHkb+PGjcyaNQtPT0/lP4+XXnpJL4kp\nvp9uDd6pU6fw9vZm+PDhtGnTxuhxmjZtStOmTRk2bBj9+/fnu+++Y/To0SbHaWtry8GDB5XXEyZM\nYMKECbi7u5Ofnw8UTaddv35duWN0+/Zt4uPj6dSpE1A0Zeru7o67uzuenp707t3baIJXVuJTu3Zt\nUlNTKSwsZMqUKcybN0+5o2pjY8P+/fv17vbdvHmTc+fOYW1tzb///suZM2fIzMzUS6KN2bFjh/Lg\niq+vL+PGjSu1bq9evZgwYYLB2rX/Vb9+/ejWrRu9evViw4YNekleacls8eTv77//xsvLi+3bt+Ph\n4WFQ19bWlgMHDtC9e3cAIiMjAWjRogUFBQX8+++/JCUl8dRTT7F69WqgaE3n6tWrCQwMBIqm6b28\nvPDy8sLOzo4FCxYYTfDK++WpJFOOrTNt2jQ8PT0JCAgwqW1jLH03mV73no9yfz0ucdyrJzl+U2K/\nuT/ygcchxJPqsVuDpzN58mRiY2NLXVB+r+327NkTW1tbg6cYy2uzZcuWBAYGMnXqVIM62dnZ7Nix\nQ6mbmZnJ+fPnadKkSYViGzFiBCkpKXz55ZfKtoKCAvLy8gA4cOAAt27d4vjx42RkZJCRkUF6ejob\nNmwgNzeXH3/8kWvXrin7Hjp0SC+G0vpWmipVqjB79mz27t1Leno6AJMmTWLBggUcPXoUgDt37jBx\n4kR69+5N48aNadGiBV5eXgQEBCjnrqCggLi4OLKzs/Xa79q1K6mpqaSmppaZ3AEMHz6cCRMm8Oqr\nr1a4L+X109fXl5kzZ9KrVy+OHz9uUnu68ueff57w8HAmT55MQUGBQd3x48ezcuVKZQ0hQF5enlI3\nOTmZVq1aKdPbGRkZrFu3Tkm4UlJSuH37tnLcX3/9laZNm5bZH1OVd+zimjRpgo+Pz31PsIUQQjwY\njyTBK75WTqPRcOjQIYM6DRs2xM/Pj8zMzPvaLkBYWBhLly5V1mKVNa1YvOzNN9/k0qVLylosXZlW\nqyU2Nlb5iAovLy98fX3p0aOHsm/JdWDfffedwbHq169PcnKysu7N3d2d7t274+3tja2tLQkJCQbr\nzxo0aEC7du3YsGEDFy5coE+fPsrHpGzevFn5aI/y+lbadnNzc0JDQ5WHApydnYmIiOA///kPDg4O\ndOnShYYNG7JgwQJln08++YQWLVrg5uaGo6MjTk5OnDp1CnNz81JjKS0OXSwNGjRg3LhxVKlSxWjs\nZY2vKWM/YMAAwsLClCRPpVIZrMELDw83iAvA09OTBg0a8MUXXxi0a2Njw5dffsnHH39Mu3bt8PDw\noFevXsrav4SEBGWKVKdTp04UFhaSlpbGkSNHeO2115RxPH36tN4T5aaO42+//UabNm2UP6NHjy73\n2CX7OWnSJG7cuGEw9g9qal4IIcS9U2VmZsrjb0KIBy4owfAOpxD/i8z9kcTGGM6qPA5OnjyJlZXV\now7jnkjslYN8k4UQQgghRCUjCZ4QQgghRCUjCZ4QQgghRCUjCZ4QQgghRCUjCZ4QQgghRCXzWH7Q\nsRCi8sl8Aj+U9kn+Jgh4suM39ZsshBDGSYInhHgoHtePsyjLk/6RC09y/E9y7EI8DmSKVgghhBCi\nkpEETwghhBCikpEETwghhBCikpEETwghhBCikpEETwghhBCikpEETwghhBCikpEETwghhBCikpEE\nTwghhBCikpEETwghhBCikpEETwghhBCikpEETwghhBCikpEETwghhBCikqn6qAMQQvz/EB046lGH\nUGG5ubnUqFHjUYdxz+5n/IU1axMyJ+K+tCWEePAkwRNCPBRzNc0edQjifxCaevZRhyCEqACZohVC\nCCGEqGQkwRNCCCGEqGQkwRNCCCGEqGQkwRNCCCGEqGQkwTNiw4YNuLi4oNFocHBw4J133lHK1Go1\nOTk5evWbN2/OH3/8AUCPHj2wsrIiOztbKe/Rowdbt25VXm/fvp3XX3+dDh064O7uzoABAzh69CgA\neXl5TJs2DXt7exwcHHBxcWHLli3KvqmpqTRo0ACNRoOjoyO9evXi/PnzRvtx/vx56tSpg0ajUf70\n7t1bKVOr1QQGBurVb9GihfK6bdu2ODg46O2v62fxMkdHR5KSkvSOffr0aYYNG0a7du1wcXHB2dmZ\n2bNnc/XqVWxsbDhy5IhS99SpU7Ru3ZorV66UdVoMhIeHY2VlhYuLCx07dqRr164sXbqUwsJCpY5a\nrcbJyUmvD3fv3lXK+vfvr9emWq0mOzubiRMnMmvWLINj9ujRg8TERL3zoPszalTRU6L3eo6cnZ3x\n9PTk119/Nehj8eMsW7as1LLs7Gyj59HR0RGtVqu37ffffwdg1KhRtGnTRq+dTZs2GZQ5ODgQFhYG\nQGRkJG+99ZZeX8aOHcvMmTPLOGNCCCEeFnmKtoTLly8TFBTE7t27adiwIQAZGRll7qNSqfRe16xZ\nk8WLFxMSEqKU6+rs2LGD8ePHk5CQgJ2dHQCHDx/mypUrtG7dmsDAQHJzc9m3bx/Vq1fn2LFj9OvX\nD7VajaOjIwAvv/wyO3fuBGDmzJmEhoayatUqo7FZWlqSmppqtMzCwoLk5GTGjRtH06ZNjfYrLi6O\nl19+ucyyY8eO4eHhgYeHB2q1msuXL+Pl5cWsWbOIi4sDICsri5iYGCwsLIiIiGD06NHs2LGDa67X\nhAAAIABJREFUKlWqMHbsWGbNmkW9evXKHGdjMQwcOJDZs2cDcO7cOUaOHMnZs2eJjIxU6m3bto2a\nNWsabePkyZOkp6crY6trd+jQoQwePJgZM2Yo5+7cuXMcPnyYXr16sX//fr3zUNK9nqPly5czfvx4\ndu3aZbSPZfVf59q1awb1srOzSUxMZODAgcq24uUBAQGMGDHC6DF0ZVlZWbi4uNClSxeCgoLw8PBg\n48aN9OzZk+3bt3PgwAElbiGEEI+W3MEr4cqVK1SrVg21Wq1ss7W1NXl/3Rvi559/zo0bNwzKo6Ki\nmDRpkpLcQdHdFHd3dy5cuMCGDRt4//33qV69OgDW1tYEBgbqJSzFOTk5ceLECZPjK6569eqMHTuW\nuXPnllqn+F2f0lhbW2NhYcHZs0UfoxAbG4urq6uSTEBRMhkaGkqNGjV44403ePnll3n//ff55JNP\neO655wzupJmqeHxNmzZl8eLFLF++nNu3b5vUh8mTJxu9U2dvb4+lpSXbt29XtiUkJNCnTx+eeuqp\nCsVYkXNkrG5Z8ZtyfgBCQkKIjIxU7l5WpB1dmYWFBXZ2dpw8eRIzMzOWLl3KtGnTOHv2LIGBgSxZ\nsoRq1aqZFI8QQogHSxK8EmxtbWnfvj02Njb4+/vzySefcPPmzQq10aBBA/z8/FiwYIFBWUZGBh06\ndDC639GjR2nWrBmWlpZ62zt06KA3palTWFhIcnJymQnoP//8ozf1VnxKFmDEiBHs27ePw4cPG+yr\n1Wrx9/dX9u3atatBOcCPP/5Ibm4uzZs3L7ePOlFRUcTHx7N06VJiYmLKrFsRVlZW1KhRg1OnTinb\nPD09lT4MGjRIr763tzd3794lOTnZoK0hQ4aQkJAAFI11YmIiQ4YMUcqPHz+uN7bR0dEGbZhyjorb\nvHmzXl2tVktiYqLecX744QejZcHBwaW2a29vj52dHbGxsQZlWq2WmJgYvWMYu96uXr3KTz/9RNu2\nbYGiu5TvvPMOrq6uDBgwQO+XFiGEEI+WTNGWoFKpSEhI4NixY6SlpbFlyxYWLVpEenq6QeJVcr/i\n/w4ICKBz586MGTPG5GObejdGl1j89ddf1KhRg927d5dat3bt2qVO0QKYm5sTHBzMnDlzDBLSsqZo\ndcmfVqvlzJkzLF++XG98ivclJiaGdevWcfPmTZYvX46DgwOWlpb4+fmRk5NDnTp1TOr3vSprilal\nUjFjxgymTJmCl5eXXpmvry/h4eFkZmZy6NAhatWqRceOHZXyl156qdQp2oqcI10Sfv36dXJycvTa\nvJcp2tL6GRoaire3N0OHDjUoK22KVpf8rVixglOnTuHv74+7u7tSrlt3N3bs2HJj6L/iyZu+LSws\npEqVJ/f34PsZ/9934PiE+felLVOU9S0cagsV0XOnPLRYhHgSSYJXCmtra6ytrRkxYgRdunRhz549\nvPHGG9StW5fr168rCcPdu3e5desWdevW1dtfrVbz7rvvMn++/n+I7dq145dffsHGxsbgmK1bt+bs\n2bNkZmbqJUs///yzXn1dYpGfn89bb73FokWLmDFjxj33dfDgwSxevJj09HST9yme/G3cuJFZs2bh\n6elJjRo1sLW15eDBg0rdCRMmMGHCBNzd3cnPz1e2m5mZlfnm8/7777Nhwwag6IECZ2fncuM6efIk\nubm5WFlZmdwXV1dXnn/+eRITE/W2161bF3d3d9auXctPP/3E4MGDTW6zIudIl4QXFhYyZcoU5s2b\np3en7X5M0QK0bNmSV199lcWLF5u8T/Hk79SpU3h7ezN8+HDatGkDFJ3D4n+XxdJ3k8nHFY+f0n+9\nffjHu7nf+JIVIcR/Pbm/mj4gf/31Fz/99JPy+uLFi1y7do0mTZoA4O7uzsqVK5XylStX0qlTJ711\nWbo33dGjR7Nz507OnTunlAUFBREdHa33pOSRI0fYuXMnTZo0oWfPnkycOJG8vDygaNp24cKFygMb\nxVWrVo2FCxeycuVKvWNUlJmZGdOmTTNIRov3pSw9e/bE1taWRYsWAUXTvikpKXz55ZdKnYKCAqVP\nprYdGBhIamoqqampRpO7kvufP3+ecePG8fbbb2NhYVGhPsycOZOICMPv2RwyZAiff/45W7du1VtT\naKqKnKMqVaowe/Zs9u7dqyTb9yu505k8eTKxsbFkZWWZ3JaurGXLlgQGBjJ16tQKH1cIIcTDJQle\nCXfv3iUiIoJOnTqh0Wjw9fVl+vTpyrqj8PBwLly4oHz0xvbt2/n000/12tBN19asWZOAgAAuXbqk\nlHl4ePDBBx8QHBxMx44deeWVV5g7dy4NGjQAiu5a1a9fn86dO+Pg4MDIkSOJiIhQnvIs/kQuwHPP\nPcd//vOfUqfpSq7Bc3FxMYgTipK0unXrGjwRXHwNnkaj4dChQ0aPExYWxtKlS7l+/Tr169cnOTlZ\nWU/m7u5O9+7d8fb21ltfVrIvFaVSqUhMTMTFxYVOnTrx5ptv0qtXL4NEtfgaPI1Go3wcS/Fj29nZ\nYWdnZxBPt27duHXrFhqNRu8urUqlMliDN2DAAL1ynfLOUfG65ubmhIaGKh9Houtj8eOEh4crZaWN\nX2nbGzZsiJ+fH5mZmXrbS67BK/5LTPG23nzzTS5duqSsAyzrWEIIIR4dVWZmZsVvAwghRAUFJRQ8\n6hBEJZG5P5LYmMf7TvLJkycrtFTkcSKxVw5yB08IIYQQopKRBE8IIYQQopKRBE8IIYQQopKRBE8I\nIYQQopKRBE8IIYQQopKRBE8IIYQQopKRb7IQQjwUmU/gtw+U9XVZT4InOf7yvqpMCFE2SfCEEA/F\n4/65ZcY86Z+p9STH/yTHLsTjQKZohRBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnw\nhBBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnwhBBCCCEqGUnwhBBC\nCCEqGUnwhBBCCCEqmaqPOgAhxP8P0YGjDLYV1qxNyJyIRxCNEEJUbpLgCSEeirmaZgbbQlPPPoJI\nhBCi8pMpWiGEEEKISkYSPCGEEEKISkYSPCGEEEKISqZCCV7btm35/fffAcjJyaFPnz6MHTuWwsJC\nRo0ahVqtVsoBzp07h1qtxt/fX9l25coVRo4ciZ2dHa6urnh4eBAXF6eU79ixAy8vL+zs7HB3d6db\nt26sXr1aKVer1Tg5OaHRaJQ/d+/eNVrm4uJCfn6+QT/Cw8OxsrLSa2PZsmXKv5s1a0abNm2U1wcO\nHNDb//z587Ro0cKg3VGjRvHZZ5/pbQsNDSUiomgReUJCAi+++CIajYYuXbowbNgwMjMzGTx4sHKs\n4n3o168fAJmZmYwdOxY7Ozs6duzI66+/zo8//qgcIyEhAbVazfr16/W2FR93gHHjxrF169ZS4wDo\n0aMHW7duNeibTlhYGM8//zzXr18HYMiQIUZjV6vVyvaXXnpJb7w3b95c6jkoqXPnzmzfvl1vW1ZW\nFo0bN+aPP/4A4PPPP0etVpORkaFXr7S+GDtPYPy6+PTTT0lLS6N9+/bk5OQodRMTE3nttdfQarUA\n/Pjjj8p4q9VqvboleXh4oNFo9LadP38etVpNYGCg3rbi11l+fj7z5s2jY8eOODk54eLiQmhoqHL9\nlzUWu3fvplu3bmg0Gjp37kzPnj3RarXlXnum/Lw5Ozvj4uJCSkpKqX0WQgjxcFXoIQuVSgUUJRwD\nBgygQ4cOzJ8/Xylr164da9asYdasWQCsXr2adu3aKfvl5OTQo0cPhgwZwqeffgrArVu3+Prrr4Gi\n5G7cuHHExcXRoUMHAC5cuMCXX36pF8e2bduoWbOm0RjLKivej4EDBzJ79my97e+++y4Ao0ePpn37\n9owYMcK0gSnWrq6vpW3r2rUrK1euRKvVMnz4cKKjo0lISFDK1Wq1QR/8/f2xsbHh4MGDqFQq0tLS\nGDp0KNu2baNZs2aoVCoaN27MvHnz8PHxwczMzCCOwsJC9uzZw/vvv8/atWuNxjFv3jyjfdApKChg\n7dq1vPbaa6xZs4axY8cSHx9fZuwAERER5OTk6I33kSNHjJ6DkoYMGcLq1avx8PBQtm3YsIEOHTrQ\nuHFjAOLj4/Hx8SE+Pp6oqKhSx96U7aXF5OnpSVhYGNHR0Vy5coU5c+bwzTffKO1s2bKFN954o8y+\nABw7doxbt25RvXp1Dh06hJ2dnVJmYWFBcnIy48aNo2nTpgb7jhkzhry8PHbt2kWtWrUoKCggPj6e\nvLw8qlatWupY3L17l2HDhpGcnEzr1q0BOHz4MCqVqtxrD0z7efvhhx94++23OX36dLljIIQQ4sGr\n8BTt33//jY+PD+7u7kpyp9OrVy+2bNmCVqtFq9Wyfv16+vXrp9zlSEpKok6dOkyYMEHZ55lnnmH4\n8OEAREVFMWnSJCW5A3jxxRcJDg7WO46uPWPKKqtIPVPbMWW/4tt0/1apVGg0Gk6dOlVme2lpaZw+\nfZrZs2cryYSTkxNDhgxh4cKFSj17e3usrKxYtWqV0Th++uknbG1tqV69+j3FAfD999/z0ksvMXHi\nRL27qqYob1xKM2DAAL7//nvlDiMU3Z0cMmQIAEePHuXWrVtERUWxfv16/v3333uOp6ztYWFhpKSk\nkJqaSkBAAOPHj6d58+ZK+bZt2/D09Cz3uPHx8fj5+eHn56eXXAFUr16dsWPHMnfuXIP9Tp8+zZYt\nW/joo4+oVasWAGZmZvj7+yuvSxuLrKwscnJyeO6555T22rZtW26sOqacJycnJ27cuMG1a9dMblcI\nIcSDU6EET6vV8uabb+Ll5cXkyZMNymvVqkWnTp3Yvn07qampWFtb8+yzzyrlv/76q17yVlJGRkaZ\n5Tqenp7KdNGgQYNMLivej8TERKVeyQTyYcjLy+Pbb7/F1ta2zHq//fYbdnZ2mJmZ6W3v0KEDR44c\nAf77Bjx9+nQWLFjAnTt3DNrZsmUL3bt3v+c44L/Jib29PYWFhfzyyy/l7lOakudAo9Hwww8/GNR7\n/vnn0Wg0rFu3DoAzZ85w7NgxvL29AVi1ahV+fn7Uq1cPOzs7tmzZ8kBiqlGjBh9//DFDhw7l9u3b\njBw5Utnv2LFj1KtXj9q1a5fZfn5+PklJSQwYMID+/fuzfv168vLy9OqMGDGCffv2cfjwYb3tGRkZ\nNG/evMxjlDYWlpaW+Pv706FDB/z8/IiJieHixYsmj0tZP1O6a2/z5s00atSIOnXqmNyuEEKIB6fC\nU7Senp58/fXXvPnmm9SvX9+gzqBBg1ixYgXm5uYMHjxYWaul278id8b8/f05ffo0V69e5fjx48r2\nBzVF+78qbWqz+PaUlBRl/VWXLl2YOHFiue2aOmatW7fG0dGRZcuWUbduXb2ybdu26a3vqmgcV69e\nJS0tTVm75uvrS3x8vEkJuTEVOQdDhgxhwYIFvP3226xevZp+/fphbm5Ofn4+69atY9u2bUDR3b74\n+Hh69+79QGJycHDA2tqa0aNH621PTk6mR48e5bb/3XffYWVlxQsvvABAu3bt2Lx5M3379lXqmJub\nExwczJw5c1iwYIHJsZc3FtHR0YwZM4bdu3fzww8/sHDhQlJSUvTuQpamrJ8pT09PsrKyuHLlChs3\nbiz1Z0AIIcTDVeEPOn7vvff49ttv8fb25ptvvtFL8nTTfUFBQeTn57N48WISExOVcltbW4NpqeJs\nbW05cOAANjY2AHzxxRdkZ2crb4j3071OwZalbt263LhxQ2/btWvX9N5E3d3dWblypclt2tjY8NFH\nH3H37l1lnRXAzz//rIxTcdOmTcPT05OAgABl2++//07dunWxtLS85zgSExO5e/cuXbp0AYrW42Vn\nZxMeHs5TTz1lcjvFmXoOdP357bffSExMVNb9JScnc+vWLeVuXmFhIVevXuXSpUs0bNiwzDZLS0TK\ni8nMzMzgbuq3337LihUryu1HfHw8x44dU+6W5uTkUFhYqJfgAQwePJjFixeTnp6ubLO1teXMmTNk\nZmbqnUed0sbi4sWLNGrUCICmTZvStGlThg0bRv/+/fn2228ZM2ZMuXGXRZf8LVq0iLCwML777rtS\n6/Zfsctg29934PiE+UZqPx5yc3OpUaPGow7jnj1u8astVETPnfKowxDi/4V7+iaLgIAAtFqtQZKn\ne3OcP38++fn5Bm+E/fr148MPP2TRokWMGzcOKHrIYv369fj7+xMcHMx7772HjY0N7du3ByA7O9vg\n+P/rGrwHkdxBUdI0ZcoURo4ciaWlJX/++Sc7d+4kKCjono/t6OhI8+bNmTFjBnPnzqVKlSqkpaUR\nHx9vdEqzSZMm+Pj4sGTJEmUMjd1hqugYrl69moSEBFxdXZVtffv2ZePGjQwYMKDMPtzr+judqlWr\nMmDAAMaOHUvt2rWVBxMSEhKIjo5m6NChSt2AgAASEhKUafeKrLW7l+vir7/+Ii8vT3ngo7S2rly5\nwo8//sixY8eUNXN5eXm89NJL/Pnnn3p1zczMmDZtGtOnT1e2tWjRAi8vLwICAli0aBEWFhYUFBSQ\nkJBA3759Sx2L1atXM3r0aPbt24e7uzsqlYrMzEzOnz9v9EEOY0wZl3HjxrFhwwYSExPx8/MzWsfS\nd5PhNpMieHQe9/jK87jFf3N/5KMOQYj/N+75q8omTpyIVqvFx8eHTZuK/uPW3RUp/sRj8ScWa9as\nyZYtW5gxYwbt2rWjVq1aVKtWjXfeeUfZLyYmhqlTp3L58mWef/55qlevzocffqh3bE9PT6pU+e/y\nwaSkJOrVq1dumbGYSlNeeWZmJm3atFFet2rVivXr1/Pmm2/yxhtvoFKpMDMzIyoqSvmoi3s9blxc\nHNOmTcPe3p5q1apRp04d4uLiaNasmdF2J02axJo1a5TX3377LbGxsXrHKCuO0aNHK3flVCoVn376\nKf/8849ecgfQv39/EhISlASvrClqY08XJyYm6n20Rvfu3Zkyxfhv90OGDGHRokXKgz1//fUX6enp\nev3SxTR27FglwSvZF90T2fPmzSMmJkbZLyYmpsIxQVHybGxtY6dOnfSu+yFDhvDqq68qyR0UTce+\n8cYbrF69Gj8/P70x6tmzJx9++KHex6188sknREZG4ubmRvXq1SksLMTT05MbN26UORajRo0iNjaW\nkJAQzM3NKSgowNfX1yDpL+38lfYzVbL+nDlzGDlyJH369FEe5hFCCPFoqDIzMx/M7SzxWLh8+TL9\n+vVjz549jzqUSqlfv35Mnz6ddu3aPepQHntBCQWPOgTxiGXujyQ2ZqpJdU+ePImVldUDjujBeZLj\nl9grh3u+gyeeDPXr15fk7gFKSkp61CEIIYQQBuSryoQQQgghKhlJ8IQQQgghKhlJ8IQQQgghKhlJ\n8IQQQgghKhlJ8IQQQgghKhl5ilYI8VBkPoEfcvu4fRNERT1u8ast5KvshHhYJMETQjwUpn7+2ePk\nSf9MrSc9fiHEvZMpWiGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYS\nPCGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYSPCGEEEKISkYSPCGEEEIoGjVq9KhD\nuGdPcuz3myR4QgghhFDUrFnzUYdwz57k2O83SfCEEEIIISoZSfCEEEIIISoZSfCEEEIIISoZSfCE\nEEIIISoZSfCEEEIIISoZSfCEEEIIISqZB5LgtW3bFgcHBzQajfLnjz/+UMocHR3RarV69X///Xfl\n9VdffYWLiwsODg64ubnx9ttv8+effyrlx48fR61Ws2TJEr3jhoeHo1ar+eWXX/S2TZ8+Xa/e559/\njlqtJiMjo8x+HD16lL59+9K+fXvs7Ozw9/fn4sWLSvmoUaP47LPPAEhISMDf39+k8YmMjKRjx444\nOjoSFhZWbv2kpCTc3d3p0KEDbm5u9OjRg61bt+rV2bZtG2q1ms2bN+ttP3z4MD169ECj0dClSxde\ne+01rl69alKcxRXvq05oaCgREREApKam4u7urpTdvn2bkJAQ2rdvj6OjI05OTowaNYpLly4Bxs/L\nsmXLGD16dKnHV6vVetfJuXPnUKvVyrifP3+eOnXq6F13vXv3BkCr1TJv3jxeeeUVnJ2d6dKlCx9/\n/LHeMTIzM6lfvz6TJ08ucyzy8/OZN28eHTt2xMnJCRcXF0JDQ7l79y5g2nVTkb44OTnh6enJ4cOH\njcbz2Wef4ejoiLOzMw4ODkyfPp2bN28qY9C+fXsaNmyovJ47dy5geM0sWLBAqfPCCy9gZ2eHRqPB\nxcWFixcvGlx3mzdvxtXVFQcHB+zt7QkNDeXff/8tc+yEEKI8fn5+1K9fn3/++afUOpMmTUKtVnPm\nzBkAsrOziYqKwtHRkYYNG/Liiy/SvXt3EhMTyzzWd999x4ABA7CysuL555+nVatWDBw40OC99ElU\n9UE0qlKpiIuL4+WXXzZalp2dTWJiIgMHDlS26cTFxbFkyRLWrFlDs2bNANizZw9///03L7zwAgDx\n8fF4e3uTkJCglxCoVCoaN27MrFmz2LRpk0HbOvHx8fj4+BAfH09UVJTRPmRmZtK7d2+ioqLo2bMn\nAEuWLKFPnz6kpaVRtWpVVCqV0fbLcvLkSb744gsOHjyIubk5Z8+eLbO+bjzi4+Np2bIlAMeOHSMl\nJaXUPr3xxhvK9nfeeYfZs2fj6ekJwNmzZ+/pc4KM9bW0/mu1Wnx9fbGxsWHv3r1Ur16dwsJC1q5d\ny4ULF2jYsGGp7ZV1/Hbt2rFmzRpmzZoFwOrVq2nXrp3efpaWlqSmphrsv3HjRvbs2cOuXbuoXr06\n+fn5yn8MOmvXrqVr166sX7+eOXPmUK1aNaOxjBkzhry8PHbt2kWtWrUoKCggPj6evLw8srKy6NWr\nF9HR0WVeNxXty9KlSxk7diy7du3Si+XAgQMsXbqUnTt38swzz6DVajl69ChqtVrZd8+ePUyfPp2d\nO3fq7VvymgkKCiIoKAiAN954g/HjxyvXje4c6OJLS0sjJCSEpKQkrK2tycvLY9SoUQQFBfHRRx8Z\nHTchxMMTHBrOzSxt+RUfILWFiui5Uyq8n5+fH1u3bmXTpk0MHTrUoLygoID169fToUMHmjdvzt9/\n/03Pnj05ceIE/fr14z//+Q+5ubls2rSJUaNGsW3bNj777DOqVPnvPS2tVsuECROIi4vDxsaGkSNH\n0qBBA65du8b333/P0KFD+eyzz+jXr9//NAaP0gNJ8AC9O3QlhYSEEBkZSf/+/alaVT+EyMhIFi9e\nrCR3AM7Ozsq/7969S1JSEtu2bcPX15eDBw9ib2+vlPv4+JCSksKOHTvo2rWrwbGPHj3KrVu3iIqK\nwtnZmXnz5hl9I//000/RaDTKmzTA6NGj+frrr1m3bh0DBgwwbSBKqFatGllZWdy4cYMGDRro9dOY\niIgIPv74YyW5A7C2tsba2lp5fePGDdLS0vjll1/o2LEjf//9N88//zwAly5don79+krd8o5XlpLn\nVKvVGj3Pu3bt4o8//mDz5s2YmZkBUKVKFYMxM9ZeWXr16kV8fDwzZ84EYP369fj7+7N///5yY790\n6RLPPvss1atXB4rOw0svvaRXJyEhgYiICD744AOSk5P1zr3O6dOn2bJlC0ePHqVWrVoAmJmZKXfe\nIiMjcXFxKfe6qWhf3NzcmDNnjsH2ixcv8swzzyixqFQq2rRpo1fH2LiWdc2UtZ9OREQEwcHBynVo\nbm7OwoULsbGxYdKkScovY0KIR+NmlhbLTiGPNob9kfe0n5eXF08//TRJSUlGE7ydO3dy7do1goOD\ngaJZkRMnTpCQkMDrr7+u1Bs5ciQzZsxg0aJF2Nra8t577yllH3/8MXFxcbz77rtERurH+d5777F9\n+3by8/PvKf7HxQOZotVqtfj7+yvTPSUTLXt7e+zs7IiNjdXbfvXqVS5dukSHDh1KbXvr1q20atWK\nF154gQEDBhAfH69XrlKpmDFjBrNnz1ZiKW7VqlX4+flRr1497OzsSr0Ne/ToUTp27GiwvWPHjhw5\ncqT0zpejZs2aPPPMM/Tp04fr16+XWffq1av89ddfZY4HwJdffomXlxe1a9fGx8eHNWvWKGVBQUF0\n796dPn36EB4ezsmTJ+8pbq1WS0xMjN7055dffmn0rtuvv/6KnZ2dktyV1l5iYqJeex9++GGZd/Fq\n1apFp06d2L59O6mpqVhbW/Pss8/q1fnnn3/02gwMDASgb9++nDhxgvbt2zNmzBi++uorCgoKlP2O\nHDnCrVu36NKlC35+fgbXlU5GRgbNmzendu3aRstNvW5M6UtxGzZswNbW1mC7h4cHVatWpW3btrzz\nzjt88cUX5ObmltqOTlnXjE5Z58JYPy0tLWnatCm//fZbuccXQojSmJub4+Pjw549e7h8+bJB+Vdf\nfUXVqlXp27cv+/fvZ8eOHQwePFgvudMJCwujRYsWxMTEcOfOHQByc3NZuHAhrVq1Ijw83GgMHh4e\neu3Fxsbi6OhIo0aNePHFF9FoNKxcufL+dPgBeehTtLry0NBQvL29jWbnZYmPj1fugvTv3x9nZ2fC\nw8OVOzMqlQpPT08++OADNmzYoPcmlZ+fz7p169i2bRuAkiDq1mkVV9rdKa1WW+Fp2eIGDx7M1KlT\nOXDgAD179uSbb74hPz+fbt26lbsmEOC1117j9u3bPPXUU+zYsQP4750nXZ/Gjh2r/KYyfvx4fH19\n2b17NykpKbi5ubF27VocHR0rFLdKpSIgIIARI0Yo26ZPn17qXZ7i21NSUpg+fTpZWVm89dZbjBs3\nDpVKxcCBA5VEHIrWkh08eLDMOAYNGsSKFSswNzdn8ODBBkly7dq1jU7R1qtXj7179/LTTz+xd+9e\n3n//fb766iuSkpKAosTf19cXKPrtMTAwkL/++osGDRqUMzKG/Tb1uimvL7pkVavV0qyqFscIAAAg\nAElEQVRZMz755BODdmvWrMm2bds4ePAg6enpxMXF8dlnn7Fz585Sp5ih7GvG1H6WprSfjxET5pvc\n/uMiNzeXGjVqPOow7tmjiv9ep+aE0PH19SUhIYF169YxZswYZXtOTg7Jycm4u7tTp04dZS2+n5+f\n0XbMzMzo168fkZGR7Nu3D1dXV/bt28fNmzcZNWqU3rRtaeLi4ggODqZXr16MHDmS/Px8jh07xk8/\n/cTw4cPvS38fhAc2RVueli1b8uqrr7J48WJl23PPPUfDhg355Zdf9Bbs6/z999/s3LmTw4cPK29O\nd+7cYePGjfTv3x/47xtPWFgY48aN05sqS05O5tatW3h7ewNQWFjI1atXuXjxosEXFNvY2PDzzz8b\nxPDLL7/wzjvv3FOfr127RkZGBoMGDWLQoEGEh4fTs2dPXnvtNYYMGWJQXzceBw4cwM3NDSi6g3ns\n2DElyT106BDHjx/XW4t45coV9u3bR+fOnQGoX78+vr6++Pr6UqNGDTZu3GiQ4AUHB7N3714AVq5c\nSYsWLQziKW8KVcfW1pbY2FgKCgowMzPDzc2N1NRUpk+fTnZ2dqntlde+SqVCo9EQFBREfn4+ixcv\nLncBbXFmZma88sorvPLKKwwZMoRWrVqRmZlJzZo1SUpK4qmnnmL16tVA0VKA1atXK3cAi/ftzJkz\nZGZmYmlpaXAMU68bU/pSWrJqjL29Pfb29rz77ru0bNmSY8eOGb3jB6ZdM+WxsbFh//792NjYKNtu\n3rzJuXPn9JYPFPeop4vuheEZfrI8qvjvdWpOCB2NRkOjRo1ISkrSS/CSk5PJzs5WfiHXPaxW/P+i\nknTLVk6cOIGrq6uyT8nlLKXZunUr1tbWrFix4p768qg8sI9JMSUZmDx5MrGxsWRlZSnbgoODmTZt\nGufOnVO2paWlceDAARITE+nZsydHjhwhIyODjIwMFi1apEynFT9mly5daN68OWvXrlXuKCQkJBAd\nHa3se+TIEQYNGqS8qRf37rvvkpqaysaNG5VtH3/8Mbdv39ZbdGlq0gNQp04d6tevz9dffw3AlClT\naNasGR988AGDBw82us+kSZOYOnUqp0+fVrZlZ2crfYqPj2fChAlKnzIyMpg8ebIyJlu2bKGwsBAo\nSoaPHz9O06ZNDY4THR1NamoqqampRpO7inB3d6dRo0ZMmTKFvLw8ZXtOTo4Sd0XGTUe3z/z585k/\nf36ZU8AlHTp0iAsXLui9VqvVWFpakpycTKtWrfjtt9+UMVy3bp3R66JFixZ4eXkREBCgXLcFBQXE\nxcWRnZ1d4evmXvpS3MmTJzl27Jjy+sSJE+Tn5xv8wlJcedeMKSZNmsSCBQs4evQoUHRtTZw4kd69\ne9O4ceN76osQQuioVCr69u3LoUOH9N7/1q5di4WFBT169AAgKysLlUrF008/XWpburLbt2/r/W1h\nYWFSLLVr1+bixYvlzjA9bh5Ygld8DZ5Go+HQoUMGdRo2bIifnx+ZmZnKtuHDhzN+/HiGDRuGg4MD\nXbp0YeXKldSrV4/Vq1crWbuOl5eX8uZd8snMGTNmKB+vcvnyZdLS0gwWzvfv39/o+iNLS0vWr1/P\nF198oawZ3LdvH+vWrdN7M9YdT6VSsW3bNtq0aaP8mT9ff0pKpVLx5ZdfEhcXh6OjI+7u7spTvwMG\nDNAbh+LjOGHCBN5++206dOjA66+/zrx585g3bx537txh3bp1BmPSt29fNm3aRE5ODhs3bqRz5844\nOzvj5uZG27Zteffddw2OYwpjU2/FtxX/99q1a4GiRNvJyYnXX3+df//9V7nzWJGncku2X3xtRMl9\nSq7Bc3FxAYoeKnjrrbfo3LkzGo2G999/n4SEBKAo8S85hp06daKwsJD09HSDOD755BNatGiBm5ub\n8hEwp06dwtzcvMLXTVl9MWUpQE5ODoGBgcrHEo0ZM4Zly5ZRp04do+Na3jVjyvo9KHrwKSIigv/8\n5z/Kz2nDhg1ZsGCBSfsLIUR5dP9PffXVVwBcv36d7du30717d2XpgYWFBVqtVknajCmZ0OkSvuI3\nl8oyYcIEnn76abp27Yq9vT0TJ040eXblUVJlZmY+2ueohRD/LwQlFJRfSVQKmfsjiY2Z+j+1cfLk\nSaysrO5TRA/fo45/xIT5j3xZxP24DpycnMjLy+Pnn38mNjaW4OBg1q1bpzy8OXv2bD744AO2bNlS\n6tryiIgIIiMj2bBhA66uruzcuZM+ffowdepU5Unc8uT+X3t3HlZVtT5w/HskAWePMhmKGmDKJCqI\ngSBqaWYCJqhkhWOTqdfp50ip2EXFa5gDFs4KIoJeKrW8jgFO3cpsUhxAb5RCIoQDiHB+f/iwL0dG\nleFw7vt5nvN4ztprr/2uLR5f1lp777t3OXDgAIcPH+bgwYP8/vvvjB8/nrCwsCfqX02SJ1kIIYQQ\nQieNGDGCS5cu8f3337Nr1y7Mzc211ugXz4CUtx67sLCQuLg41Go1vXr1AuC5556jZcuWxMXFKUuY\nKtOoUSN8fX1ZuXIlZ8+eJSAggPXr15d5la+ukARPCCGEEDrJ39+fBg0aEBYWxunTpxk6dKjW8pXi\nJ15FRUVx4MCBUvuHhIRw6dIlpkyZgpGREQDGxsZMmzaNlJQU5s2bV+ZxDx8+rDy5JysrS2ubgYEB\ndnZ2ABU+baOu1dlVtEIIIYQQFXn66afx8PBg//79AGU+ZGDdunX4+voSGBiIv78/zz33HHl5eXz+\n+eccP36cYcOGMXnyZK19Jk2aREpKCuvWrSMpKQk/Pz/Mzc2VdX6JiYls2LABgKFDh2JmZoabmxtm\nZmakpqYSGRmJg4NDqRvm6xJJ8IQQQgg9o26qqvPb1aibPv49Y0saPnw4iYmJ2Nra4uzsXGq7ubk5\nhw4dYvXq1SQkJPDZZ5/RsGFD7O3tiYiIKPceeatWreKll15i06ZNREREkJOTQ8uWLenRowdRUVG8\n9NJLAIwdO5Zdu3axbt06cnNzadOmDa+99lqV1+/VFbnIQghRK+Qii/8dcpFF/Y9f1H+yBk8IIYQQ\nQs/IFK0QolZk18OnG8ijyh5PdU3NCSEenyR4Qoha8aRTdnWhvk+z1ff4hRCPT6ZohRBCCCH0jCR4\nQgghhBB6RhI8IYQQQgg9IwmeEEIIIYSekQRPCCGEEELPSIInhBBCCKFnJMETQgghhNAzkuAJIYQQ\nQugZSfCEEEIIIfSMJHhCCCGE0BlRUVGo1WrlZWJigr29PRMnTuSPP/4AIDExUdm+c+fOMtvx8fFB\nrVbj5OSklN29e5fIyEiGDh1K586dadeuHV5eXmzcuJGioqIqxefo6KgVX/Fr2rRpT975aiSPKhNC\nCCH0zNLg2TS4k1OnMRQ1bsGskCWPvf+cOXPo2LEjeXl5nDx5kpiYGJKTkzlx4oRSx9jYmLi4OEaM\nGKG17x9//EFSUhLGxsaoVP99NnJqaiqzZs3C29ubiRMn0rx5cw4ePMj06dM5ffo069atqzQulUqF\ng4MDkydP1iq3sbF57L7WBEnwhBC1Ymnw7Cf6shdCVF2DOzks9uxYpzHMT0x9ov379+9Pjx49AHj9\n9ddRq9WsWbOGffv2YWZmBsALL7zA/v37uXHjBq1bt1b2jY+Pp1mzZnTv3p1Lly4p5RYWFpw4cYJn\nn31WKQsKCuK9994jKiqK6dOnV/r8Zo1Gg4WFBQEBAU/Uv5omU7RCiFpR16MJQoj6zdPTE4CrV68q\nZS+++CKNGjVi9+7dWnV37dqFr68vhoaGWuWtWrXSSu6KDR48GICUlJQqxaLRaCgoKOD27duP1Ifa\nJAmeEEIIIXReauqDEcFWrVopZcbGxgwePJi4uDil7MKFC5w9exZ/f38ArSna8mRkZABojQJWJDk5\nmTZt2tC2bVscHR1Zu3ZtlftRWyTBE0IIIYTOycnJ4caNG6Snp7N7926WLVtG48aNGThwoFJHpVIR\nEBDA6dOnlZG92NhYnn76aWXErzL37t0jIiICKysrXF1dK63v4ODA3Llz2bZtG6tWraJdu3bMmzeP\n+fPnP15Ha4iswRNCCCGEzhk2bJjW5y5durBkyRIsLCy4cOGCUu7t7Y2pqSm7du1i+vTpxMfH88or\nr1Rp5A5g5syZnD9/ntjYWAwMDCqtv2PHDq3Pr732Gv7+/qxbt4633nqLdu3aVem4NU0SPCGEEELo\nnGXLltGpUyeMjY1p27YtlpaWZdZr0KABfn5+xMXF0adPH1JTU5Xp2cp8/PHHbN26lfnz5/PCCy88\ndqzvvvsuhw4dIikpicDAwMdupzrJFK14ZI6OjnTu3FnrnkHF9y2KjIxUPltZWeHp6am8Fi5cSFRU\nlPK5Y8eO2NvbK5+/++47AMaMGYONjQ3379/XOq5arebOnTuVxvfdd9/h5+dHt27d6NevHz4+Phw/\nfhyAoqIi/vGPf+Di4oKbmxu9evVi69atyr5XrlxBrVYzffp0rTJra2vgwVVdnp6e9OrVi9atWyux\nv/feewCcP38etVpdaj1GaGgowcHBwH/v37Ry5Uple2JiIn379tXqq4eHh9b5Kz4fxdt69+6Nl5cX\nR48eLfdcFBQU8OGHH+Li4oKHhwdeXl7Mnz9faeuXX35h2LBhdO/eHWdnZ4KCgkhPT1f2f+edd5S/\no549e/LBBx9otf9wLMeOHavkb0cIIaqme/fu9OnTBzc3t3KTu2IBAQGcO3eOhQsX0qlTJ7p27Vpp\n+1FRUSxYsIBx48Zpfec/jqeffhqAmzdvPlE71UlG8MQjU6lUtGnThkOHDim/8URHR+Ps7Kw1JN6v\nXz82b95cav9Ro0YBD37j6d69O+PHj1e23bx5k+TkZJycnNi3bx8+Pj6PFNvPP//MiBEj+PTTT5WE\nKS0tjbNnzwKwfPlyEhMTOXToEC1atCA9PR1/f3+MjY0ZPnw4AE2bNmXfvn1MmjSJDh06aLV/6NAh\n4MFVXH379iUxMVFr+/bt2xkyZAhRUVG8++67WuesJAsLCyIiIhg9ejQtWrQosy//+te/aNy4cYXb\nDh48yLhx47RuA1DSxIkTyc/P59ixYzRp0oTCwkK2b99Ofn4+t27dws/Pj7CwMHx9fQFYu3Ytr7zy\nCsnJyTz11FOoVCqmTp3K+PHjuXXrFl5eXvTq1YtBgwaVimXfvn2MHTu23FiEEKKmuLq60r59e5KS\nkpg7d26l9ffu3cvkyZPx8fFh+fLlT3z8tLQ0AExMTJ64reoiI3jisQQGBhIdHQ08+MG+e/cuXbp0\nQaPRKHVKvi/Pw3ViY2MZNGgQQUFBREVFPXJcK1eu5I033tAaDevQoQM+Pj7k5eURHh7ORx99pCRV\nlpaWhISEEBoaqtQ3NDTkvffeY/HixVWOG+D+/fvExcXx97//HY1Gw/fff1/u/hYWFvj6+mqN4lXl\nGA/z8PAgKyuLP//8s9S2S5cusXfvXj7++GOaNGkCgIGBAUFBQTRp0oRPPvkELy8vJbmDB0l3s2bN\niI+PLxVH06ZNcXZ2Lvc2At7e3mRlZZGVlVVp3EIIUd2WLFnC7NmzlUGE8iQnJzNu3Dh69+6tzDqV\n5f79+6SkpHD9+nWlLDs7m8LCQq16BQUFhIeHY2hoiJeX15N1ohpJgiceS+/evfnll1/Izs4mOjqa\nkSNHlqpz9OhRrSnGbdu2VdpuVFQUI0eOZNCgQXz77bdcu3btkeI6e/ascmPMh12+fJmGDRuWutu4\ni4sLaWlpWtO/48eP59SpU/z4449VPvZXX31Fp06daNu2LSNGjGD79u0V1p8xYwbbtm3T+vIoacCA\nAcq5e/XVV7W2FSddX3zxBZaWlmVe2n/27FmeeeaZckcIf/nlF1xcXEqVu7i48NNPP5Uqz8zM5PTp\n01qP/SkZy549e7C0tNS6hYEQQtSWF198kVmzZinTpcVK/rJ89epVAgMDadCgAT4+PuzevZudO3cq\nr59//lmpm56ejpubGwsXLlTK9u7di4uLCwsXLmTTpk2sWLGCPn36cOrUKWbOnImFhUXNd7SKZIpW\nPBaVSoWfnx/x8fHs2bOHAwcOcObMGa2pSG9vb7Zs2VLlNn/44Qf++usvnnvuOQCGDBnCjh07mDp1\narXEXNmIWMntRkZGzJw5k5CQkCoP32/fvl15XE5AQAC9e/cmNDS01I02i5mamhIUFERYWBh+fn6l\ntlc0RTtgwABu3brF9evXSUhIqPLVYiVpNJoyz4lGo1Ha02g0hIeHs2nTJi5evEhQUJDW6GhxLA0a\nNMDc3PyxRl2FEOJhVflOq+r3Xsl6V65cITc3F5VKxYwZM0rVmzVrFvb29uXub29vT+fOnYmNjeXP\nP//E0NAQBwcHNm3aVOb3eF2SBE88FpVKRWBgIM8//zweHh6o1eonbnP79u3cvHlTGSG6d+8eTZs2\nfaQEz8nJiW+//ZaXXnqp1DZra2sKCgq4cOGC1qNovvnmGzp06ECTJk20pjpHjRrF6tWrlQs0KpKR\nkcGRI0f48ccfWbLkweO48vLySEhIqPBxNpMmTcLNza1KC4JLKk7+Vq1axQcffMCXX35Zqo6TkxOX\nL18mOzubli1bltru4ODAv//971Ll3377LRMmTADQWoN38eJFhgwZwujRo7W+ACtKREtK/Okq5//2\n90fpZp27e/cujRo1quswHltNxa9uqiJs8Zxqb1dUn6LGLZ74UWHVEcPjGDVqVKXTrJ6enlVaDrJz\n585S+1X1Qoj27duXquvs7FzqNim6ShI88dg6dOhAcHCw1pRoVdaNlSU/P5/4+HiOHTumdWGDq6sr\nJ06cUEb1Kmt/8uTJ+Pn54eXlRZ8+fYD/XmTh4+PDlClTmDp1Ktu3b6dly5b89ttvfPDBB8yePbtU\nWwYGBsybN0+5+rUiMTEx+Pr68sknnyhl8fHxbN26lYCAgHLjbtGiBRMnTiQsLKzUNGtVzuWkSZP4\n5z//SUxMTKlpcmtrawYNGsTUqVNZtWoVTZs2pbCwkKioKIYNG8abb75Jz549SUhIUNbhrVmzhtzc\nXK1bDBTHYWNjw/Tp05k7dy4JCQmVxvawTm989sj71LXSaXH9UlPx3/xmaQ21LKqLPPdZyBo88USC\ngoJwcHBQPhcPZatUqlJr8KZMmVJq/+L6e/fuxdrautRVqwEBAVrTfq6urtjb22Nvb0/Pnj1Ltefg\n4EBMTAwrVqygW7duuLu7M3nyZMzNzQH4v//7P7y9venfvz9ubm5KolM8tVoyJgBfX19MTEzKnAoo\nWRYdHa1chVts0KBBnDlzhqtXr6JSqbTql3z/5ptvUlRUVOoYJdfgeXp6Kmv1Hq4XEhLChx9+yL17\n90rFGBERgbW1Nd7e3ri7u+Ph4cHFixcxMjKiZcuW7Nmzhy1bttCtWzecnZ05deoU8fHxWjf7LHm8\nMWPG8Pvvv3Pw4MEyYxFCCKEbVNnZ2Y835CKEEI9gRlRh5ZVEvZD9zVLWh1d+K4on8fBSivqmvscv\n6j8ZwRNCCCGE0DOS4AkhhBBC6BlJ8IQQQggh9IwkeEIIIYQQekYSPCGEEEIIPSMJnhBCCCGEnpEb\nHQshakV2Pbw5rjzJomzqpnL/Q312586dKj2dRhfV59irmyR4QohaUdP3TasJ9f1eZvU9flE30tPT\n6+3PTX2OvbrJFK0QQgghhJ6RBE8IIYQQQs9IgieEEEIIoWckwRNCCCGE0DOS4AkhhBBC6BlJ8IQQ\nQggh9IwqOztbU9dBCCGEEEKI6iMjeEIIIYQQekYSPCGEEEIIPSMJnhBCCCGEnpEETwghhBBCz0iC\nJ4QQQgihZyTBE0LUmPXr1+Pk5ISFhQXe3t6cOHGiTuNJTk5m5MiR2NnZoVariY6OLlUnNDSULl26\n0KZNG15++WXOnTuntT0/P5+ZM2dibW2NpaUlgYGB/P7777US/4oVK+jbty9WVlbY2NgwcuRIfv31\n13rRh8jISDw8PLCyssLKyooBAwZw4MABnY+7LCtWrECtVjNz5kytcl2NPzQ0FLVarfXq3LlzvYgd\n4Nq1a7z99tvY2NhgYWFBr169SE5O1vn4HR0dS513tVrNiBEjANBoNDUatyR4QogasXv3bubMmcOM\nGTNITEykZ8+eBAQE8Ntvv9VZTHfu3MHBwYHQ0FAaNWqESqXS2h4eHs7atWtZtmwZhw8fxtTUlKFD\nh3Lr1i2lzpw5c/jiiy/YuHEj+/btIzc3lxEjRlBUVFTj8ScnJzNhwgQOHDjAZ599xlNPPYWfnx/Z\n2dk63wdLS0sWLVrE119/zdGjR/Hy8mLUqFH8+OOPOh33w7755hu2bNmCvb291s+PrsffqVMnUlJS\nlNfx48frRezZ2dkMHDgQlUrFrl27OH36NMuWLcPU1FTn4z927JjWOT927BgqlYqhQ4cCsHLlyhqN\nW+6DJ4SoEf3798fR0ZHw8HClrEePHvj6+vL+++/XYWQPtG3blrCwMAIDA4EHv0137tyZt956i2nT\npgGQl5eHra0tISEhjB49mpycHGxtbVm7di3+/v4ApKen4+joSFxcHP369avVPty+fRsrKyuio6MZ\nOHBgvetDx44dWbBgAW+88Ua9iDsnJwdvb29WrVrFkiVLsLOzY9myZTp/3kNDQ/n888+1krpiuh77\nokWLOHHiBPv37y9zu67HX9Ly5ctZvXo158+fx9DQsMbjlhE8IUS1u3fvHj/88AN9+/bVKu/Xrx+n\nTp2qo6gqduXKFTIyMrS+NI2NjXF3d1diPnPmDAUFBVp1LC0tefbZZ+ukX7m5uRQVFdGyZUug/vSh\nsLCQ+Ph48vPzcXd3rzdx/+1vf8PPz4/evXuj0fx3bKQ+xJ+WlkaXLl3o2rUr48aNIy0trV7Evnfv\nXrp3786YMWOwtbXF09OTyMhIZbuux19Mo9Gwbds2hg8fjpGRUa3E/VT1d0MI8b/uxo0bFBYWYmZm\nplVuYmJCRkZGHUVVsevXrwNoTf3Ag5ivXbsGQEZGBgYGBrRq1UqrjqmpKZmZmbUTaAmzZ8/GycmJ\nnj17Arrfh59//pkBAwaQn59Po0aN2LRpE7a2tsp/VroaN8CWLVtIS0tj/fr1AFrTs7p+3l1dXYmI\niMDW1pbMzEzCwsIYOHAgJ0+e1PnY09LS2LBhAxMnTmTatGmcPXuWWbNmATBhwgSdj7/YkSNHuHr1\nKkFBQUDt/MxIgieEEJV4eK2eLpg7dy6nT59m//79VYpPF/rQqVMnkpOTycnJISEhgXHjxvH5559X\nuI8uxH3hwgVCQkL48ssvMTAwAB6MyJQcxSuPLsT//PPPa312dXWla9euREdH4+LiUu5+uhB7UVER\nPXr0IDg4GHhw4cLly5dZv349EyZMqHBfXYi/2JYtW+jRowf29vaV1q2uuGWKVghR7Vq3bo2BgUGp\n0brMzEzMzc3rKKqKFcf18G/GmZmZykikmZkZhYWFZGVladXJyMgoNVpZk+bMmcOePXv47LPPaN++\nvVKu631o2LAhHTp0oGvXrrz//vu4uLgQGRmp83GfPn2aGzdu0KtXL0xMTDAxMeH48eNs2LABU1NT\nWrdurdPxP6xx48Z07tyZ1NRUnT/3FhYWPPvss1pltra2ysVauh5/cSz79+/njTfeUMpqI25J8IQQ\n1c7Q0BBnZ2eOHDmiVX7kyBHc3NzqKKqKtW/fHnNzcw4fPqyU5eXlcfLkSSVmZ2dnGjZsqFUnPT2d\nlJSUWuvXrFmzlOTOxsamXvahWGFhIUVFRXTo0EGn43755Zc5ceIESUlJJCUlkZiYSLdu3fD39ycx\nMRFra2udjv9heXl5pKSkYG5urvPnvlevXqSkpGiVXbx4ESsrK6B+/MxHR0djbGysXChRW3EbzJ49\ne0H1dUMIIR5o1qwZoaGhmJubY2xsTFhYGCdPnmT16tU0b968TmK6ffs2586d4/r162zbtg07Ozua\nNWtGQUEBLVq0oLCwkI8++ggbGxsKCwuZN28eGRkZhIeHY2hoiLGxMdeuXWP9+vU4ODiQk5PD1KlT\nadGiBQsXLqzxKaEZM2awc+dONm3ahKWlJbdv3+b27duoVCoMDQ1RqVQ624cFCxZgZGREUVER6enp\nREREsGvXLhYtWkTHjh11Nm54sPi9eOTOxMQEU1NTYmNjadeuHa+++qpOn3eA+fPnK+f+4sWLzJw5\nk9TUVMLDw2nevLlOx96uXTuWLl2KgYEBFhYWHDt2jMWLFzNt2jS6d++u8+deo9EwceJEXnzxRYYM\nGaKU10bcsgZPCFEjhg4dSlZWFsuXL+f69evY2dkRGxtL27Zt6yym7777Dh8fH+DBF2xoaCihoaG8\n+uqrrFmzhilTpnD37l1mzpxJdnY2Li4u7N69myZNmihthIaGYmBgwJgxY8jLy6NPnz58+umntbLe\nZ8OGDahUKnx9fbXKZ8+erSw819U+ZGRk8Oabb5KRkUHz5s1xcHAgPj5eudJaV+Muj0ql0jquLsf/\nxx9/MH78eG7cuIGJiQmurq4cPHhQ+beoy7F369aNqKgoFi1aRFhYGO3atWP+/PmMGzdOqaPL8Scm\nJpKamqpcnFNSTcct98ETQgghhNAzsgZPCCGEEELPSIInhBBCCKFnJMETQgghhNAzkuAJIYQQQugZ\nSfCEEEIIIfSMJHhCCCGEEHpGEjwhhBBCCD0jCZ4QQohq4+joSM+ePenduzfu7u7s3r37kdtISkoq\n9Zi7uuTo6Mi5c+fK3DZ8+HDS0tIAGDx4MF999RUA77zzDpGRkQBs2rSJtWvX1kqsQhSTJ1kIIYSo\nNiqViq1bt9K5c2fOnj3LwIED6du3L2q1ukr7379/n8TERO7cuaM85aI2FRYWYmBgoFWmUqnQaMp+\nJkBsbKxWveInDJR8P2bMmBqKVojyyQieEEKIGuHk5ETTpk1JS0sjODiYfv360bt3b3x9ffnPf/4D\nwJUrV3jmmWcIDg6mT58+bNy4kc2bNxMTE4OnpycrV64kMzMTX19f3N3dcXd3Z3G36goAAAPKSURB\nVO7cuWUez9HRkYULF+Lt7U337t2VETSACxcuEBAQoMQQFRWlbFOr1SxZsoR+/fqxdOnSMtuOjY0t\ns92KRveKhYaGEhwcDDxIIOfPn6/0JTg4mKKiIuDBqN+0adPw8fGhR48evP3221U4y0KUTUbwhBBC\nVKvi0a6vv/6a/Px8rK2tmTp1KiEhIQBs3bqVBQsWsGHDBgBu3rxJjx49lO1ZWVncuXOHRYsWAbBm\nzRqeeeYZEhISAMjJySnzuCqVij///JOjR4+SmZmJl5cXHh4edOrUifHjx7N+/XpsbW3Jzc2lb9++\nuLm5YWNjA0Djxo05fPhwuX0qq107O7uqPRO0xGje5s2b+emnn/j666/RaDT4+/uzefNmxo4dC8Cv\nv/5KQkICKpUKLy8vjh49ire3d6XHEOJhkuAJIYSoNhqNhqCgIIyMjGjWrBnbtm2jefPmxMTEsGHD\nBm7fvs39+/e19jE2NsbPz69UO8V69uxJREQE77//Ph4eHvTv37/c47/++usAmJqaMmDAABITE2nQ\noAEXLlxQkiiAgoICzp8/ryR4gYGBFfarrHbt7OyqcEa0+3Ls2DFGjRrFU089+O931KhRfPHFF4wd\nOxaVSsXgwYMxNDQEHoyApqamSoInHoskeEIIIapNyTV4xa5evcq8efM4cuQIVlZWnDp1igkTJijb\nGzduXGGbrq6uJCUlcfjwYXbu3El4eDj79+8vs27JZEqj0SgjZ61atSIxMbHcYzRp0qTCGMprtyoe\nrltRW0ZGRsp7AwODUsmwEFUla/CEEELUqNzcXAwNDTEzM6OoqIiNGzdWWL9Zs2b89ddfyucrV67Q\npEkTXnnlFRYvXsyZM2fK3Tc6Ohp4MKV68OBBPD09sbW1pXHjxuzcuVOpl5KSQm5ubpXi12g0ZbZb\nlf2K/yx+7+3tzY4dO7h//z4FBQXs2LGjTi4mEfpPRvCEEELUKHt7e3x9fXFzc6N169a88MILnDx5\nUtn+8AjXyy+/zGuvvYanpyfDhg3D1NSUNWvWYGBgQFFRER999FG5x2rdujXe3t789ddfTJs2jS5d\nugAQExPDnDlz+PjjjykqKsLMzIzNmzeXefyHqVQqTExMymy3sv2K/yx+P3r0aC5fvoyXlxcA/fv3\nJygoqNxz8SgjhUKUpMrOzi772m8hhBCiHnFyciI2NlZreliI/1UyRSuEEEIIoWdkBE8IIYQQQs/I\nCJ4QQgghhJ6RBE8IIYQQQs9IgieEEEIIoWckwRNCCCGE0DOS4AkhhBBC6BlJ8IQQQggh9Mz/AwiC\nQJQvbRc1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109829f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "VOCchart = top_VOC.plot(kind=\"barh\", \n",
    "                        figsize=[9, 6], \n",
    "                        width=0.6, \n",
    "                        color=[\"cornflowerblue\", \"#FFA07A\"], \n",
    "                        edgecolor=\"k\", \n",
    "                        grid=False) # New parameter: turn off grids\n",
    "\n",
    "VOCchart.set_title(\"Top VOC emitters in Colorado\")\n",
    "VOCchart.set_xlabel(\"Parts per billion\", fontsize=11)\n",
    "\n",
    "# Get rid of the y-axis title\n",
    "VOCchart.set_ylabel(\"\")\n",
    "\n",
    "# Make the y-axis labels a bit smaller\n",
    "VOCchart.tick_params(axis=\"y\", labelsize=11)\n",
    "\n",
    "# But turn on grids only for the x-axis\n",
    "VOCchart.xaxis.grid(True)\n",
    "\n",
    "# Tweak the legend. loc=4 means lower-right corner\n",
    "VOCchart.legend([\"VOCs\", \"PM2.5\"], loc=4)\n",
    "\n",
    "# To save, we'll first call the tight_layout method to ensure nothing gets cut off.\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"VOC_chart.png\", dpi=160)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Want to save it as an SVG? No problem. Just change the file extension:\n",
    "\n",
    "`plt.savefig(\"VOC_chart.svg\", dpi=160)`\n",
    "\n",
    "Also works for .PDF, .EPS, .PS, .SVGZ, .RGBA, .RAW, and others. [More on saving figures here](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.savefig).\n",
    "\n",
    "Now let's put everything together and create a reusable function that churns out charts quickly. This time, we'll create a scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def scatter_plot(dataframe, x, y, title=\"\", xlabel=\"\", ylabel=\"\", color=\"g\", ylim=None):\n",
    "    ax = dataframe.plot(kind=\"scatter\", figsize=[7, 7], x = x, y = y, color=color, \n",
    "                        edgecolor=\"k\", ylim=ylim )\n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(xlabel, fontsize=12)\n",
    "    ax.set_ylabel(ylabel, fontsize=12)\n",
    "    plt.show()  \n",
    "    \n",
    "    # It's necessary to call plt.show() in functions or outside a Jupyter notebook.\n",
    "    # When using matplotlb inline, it's redundant."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that the function is created, use it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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sTWCoz1BCng9Bp9OVHL8GxAN+QG/YsKckGM/sU3/kmUdIy0qD3uqatKw0y+bA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w9C0b4UFRWp/coGaM85MplMRN8YTfSN0ZhMJkwmE7OnzMb/uD83B9zMgCsGkNk3U4xjAJzrfQ7/\n4/7ETYmzHTemdgzFWjFF4UVQJYbspSUvUVFRwYuvvUjO3hxGDh1p09r3lqQVSYZ7F4UUcfHQRcaM\nGNOs6wLk7M1hT9UeiU4AVMHkXpNZ+vRSRg4dSUpqiuH6zvM0cuhIst7M4lzvc4ZnTklNYVPvTS7z\nFX1jtG2+Hef3pSUvtej3Xv2+NYyao9ZDefoKRQfHXSa5Y6QgaUWSW48WjBGFRC3RJWLQ3IS1A18d\nMJbHVcBHOz8ibXsaWrTW5OtC/R63t4l2DSVresLbSIxC0dlQnr5Craq9oL3myGrgNvXexJ6qPWS9\nmcXsKbMNnnN9Hq2zd231fvfn72d//n5yvsjhsz6f1evxesPR40fJ25EHVwLnge1QFlFGRVRFs65r\nHa87j/vF11706Kk7X8PR+2/MfLUW6vetYdQctR7K01dcFrRmXXV7kvxqMsdqjon2/HXuM8m99Wid\nPWRzjll61ge7HOo1iY8nkrU/C8thC5wFZiJjbSFaw+NuTgRAoejsqOx9RafHOct7ZsLMTpmR7ZxR\nrmkaaTvSRLt+OLADqHB/bn2d5hxxrmXXojXMu83N6kJnNpvJfD2TxdGLGd1X73txHaK534jrNiab\nviW655nNZts5KakpnfLnRaFoCsrTV3R6Loe6anf71FNGT5F9casnHg3mrWYWbWi5TPL4uHhbWLup\nHq91wRE7MZYnlz8pzzBBxhofF0/iqkSP122sGE5jPPX6IkBKgEfRVVFGX6HoALhbuPT+qreLhnx8\nXHyTDZO7xLiGDHJjCAkJsRvjYFi0wbtFRFMWbd6E/T0Z9sthoahQNAUV3ld0eloi3NsRGXfdOJfn\nSlzY9IY5jREFas49GtpmaCuctzNaSpBIoejMKE9f0elpi8Ss8+fP19vdrSWozwtPJLFFn6sjlqK1\nhxiOEuBRdFU6XZc9RcujOlp5RtM0pj46lcIbCoGmdW1zd03nvebOXoHQnJ+j1nj2hjopttd8q9+3\nhlFz1Hooo69Qv2AN0JhWuN7QkDHqrOTl5ZG5W7rpNdeItpRBdr4OeNeSuDVRv28No+ao9VDhfYWi\njbkck8g0TeOxZY/ZoiHNyYZvycx6x+0MlbGvUKhEPkUnxF09e2t0TLNet7ysnAH7B1x2iYItSUpq\nihj8Fkiaa60EPJXYp1AoT1/RyXD21j5Z+AnUSgc2aDnvzfk+A2oHkNAtAZPJ1OyEOpVEplAo2gvl\n6Ss6Fc7emmWUBYuPpdW9wlNRpzCZTC1SitYWpXNtzaJ5ixh0aFCLRENaqwTzci3tVCgag/L0FYp2\noKHSuc6W3W82m3ltyWv2RL5mRENaqwRTae4rFCp7X0HnypR1DrtH5kcawvstlQnvfJ9Bhwax9fWt\nbWIk3GX3pyalMm/pvA6d8d+Zfo7aEzVPDaPmqPVQnr6iU+Hira12KsNqJa8wdklsmxlYd9n9Tzz3\nxGWX8a9QKNoeZfQVnQ53ofHWMH6O9ykoKGjx6ysUCkVboxL5FIoOhruEs5UvrFRJaAqFotkoT1/R\nIenISWutTX0JZyoJTaFQNBdl9BUdjq6onOZukeO8ZdERm+V0JLryQlGh8BYV3ld0OLqacpp1kbO8\ndDnLS5czM2FmiyoLtjZW5cKUt1LabdydfQ4VirZCGX2Fop3pzIscR2P7Rvc32s3YduY5VCjaEmX0\nFW2Gtxr5Sjmt86CMrULRuVBGX9EmNCb8ejnK1HpCLXKaj5pDhcI7lCKfok3Ur1q6J31b09pz1FmT\n0NypB7bXIq2zzKFSm2sYNUeth8reVyg6AJ01M9+xlLBIK+LZVc+2m7HtrHOoULQlKryvaBNU+PXy\nxWpsF83vuN61QqEQlKevaBOUuIxCoVC0P8roK9oMFX5VKBSK9kWF9xUKhUKh6CIoT1+haAKdJVNc\noVAoHFFGX6FoJF2xN4BCobg8UOF9haKRKBU6hULRWVFGX6FQKBSKLoIy+gpFI1GaAwqForOi9vQV\nikaiNAcUCkVnRRl9haIJKM0BhULRGVFGX6FoJVRZn0Kh6Ggoo69QtAKqrE+hUHREVCKfQtEKqLI+\nhULREVGevqLFUOFshUKh6NgoT1/RIljD2ctLl7O8dDkzE2aiaVp7D6vdUGV9CoWiI6KMvqJFUOFs\nWfgkrUgiaUUSAOmr0lkcvJjFwYvVfr5CoegQqPC+QqHTnO2J+hL3VFmfQqHoSChPX9FsNE2jvKwc\nc46504azm7s9oSIdCoWiM6CMvqJZWI3lqtpVaBM0zFvNJHRL6HThbGW0FQpFV0AZfUWzMBjLcNCm\naphMpk5l8FsClbinUCg6A8roKxQ032hb9fhV4p5CoejIqEQ+RbNYNG8RWxK22BLYhn0zjEWrOp+H\n2xJNdJQev0Kh6Ogoo69oFpdTxzlltBUKxeWOMvqKZqOMpUKhUHQO1J6+QqFQKBRdBOXpKxSNQPUX\nUCgUnRll9BUKL1HtchUKRWdHhfcVCi9RAj4KhaKzozz9LkJERATlPcsBMF0wcfr06XYekUKhUCja\nGuXpdwEiIiIo718ODwIPQnn/ciIiItp7WJ0OpbqnUCg6O8rT7wKU9yyH25GwNMDtUP52eXsOqVNy\nOWkSKBSKroky+gpFI1CaBIqmYq38KNKKePbpZ9WCUdEuKKPfBTBdMFG+Wff2ATbLewqFom0wVH50\nhz0Je1Tlh6JdUHv6XYDTp09j+tEEbwNvg+lHlcin6FhomkbSiiSSViShaVp7D6fFUZUfio6C8vS7\nCMrIKzoqSv9AoWg7lKevUCjala7gBavKD0VHQRl9hUKhaGWslR+LgxfzcM3DKpKhaDeU0VcoFO1K\nV/GCrZUfi+arUk9F+6H29BUKRbui9A8UirZDGX2FQtHuKP0DhaJtUOF9hUKhUCi6CMroKxQKheL/\nb+/+Y6uq7z+Ov679ShjtKretBSxeg22xBboClnYOqEBaC5ahTjAgUtlgbS5uEZBgoGyJ0FBHaQo6\nWmWMMNyMLlr/gWzEFYYoY3cKo0IopU5+Blt6ZyutNZhyv38Q7rz2x0Vaes7t5/lISNrPOfect+8c\n7yvnRz8HhrBd6O/YsUMzZ86Uy+WS0+nUuXPnOqzT1NSk/Px8uVwuuVwuFRQUqLm52YJqAQAIHbYL\n/ba2NmVlZWnVqlVdrrN48WIdO3ZMlZWVevvtt1VdXa2CgoI+rBIAgNBjuwf53O5rf6pz5MiRTpef\nPHlSVVVV2rNnj9LS0iRJZWVlmjFjhurq6pSQkNBntQIAEEpsd6YfjMfjUUREhNLT0/1jGRkZCg8P\nl8fjsbAyAADsLeRCv6GhocPf8DocDsXExKihocGiqgAAsL8+ubxfVFSk0tLSbtfZtWuXJk6ceMtq\nOHXq1C3bdn9Af4KjR8HRoxtDn4KjR11LTEy86c/2SegvWbJEc+fO7XaduLi4G9pWbGxsh1dv+nw+\nNTY2KjY2tsvP9aRJ/d2pU6foTxD0KDh6dGPoU3D06Nbpk9CPiopSVFRUr2wrPT1dLS0t8ng8/vv6\nHo9Hra2tysjI6JV9AADQH9nu6f36+nrV19errq5OklRTU6PPP/9cLpdLgwcP1n333aesrCwtXbpU\nmzdvls/n07JlyzR9+nTFx8dbXD0AAPZluwf5tm/frgcffFD5+flyOBx64oknNGXKFP3lL3/xr/O7\n3/1OY8aM0eOPP67Zs2crJSVFr776qoVVw868Xq+KNhWpaFNRh1tD6Lnr/a3YWUF/AZtzNDU1+awu\nAtbqz/fPvF6vcpfkqmZ0jaRrr229mXeZ9+ce9URv9dckHEvB0aNbx3Zn+kBvqnit4logRUqKlGpG\n1/hf4Yqeo79AaCH0AQAwBKGPfs29wK2k40nSF5K+uHb52b3AbXVZ/Qb9BUKL7Z7eB3pTdHS0dpfv\n9l9ydpe7ud/ci77Z3/96/6vC8kL6C9gYoY9+Lzo6WmuWrrG6jH7ren9PnTpF4AM2x+V9AAAMQegD\nAGAIQh8AAEMQ+gAAGILQBwDAEIQ+AACGIPQBADAEoQ8AgCEIfQAADEHoAwBgCEIfAABDMPc+EMK8\nXu//Xia0gJcJAegeoQ+EKK/Xq9wluaoZXSNJ2rVkl3aX7yb4AXSJy/tAiKp4reJa4EdKipRqRtf4\nz/oBoDOEPgAAhiD0gRDlXuBW0vEk6QtJX0hJx5PkXuC2uiwANsY9fSBERUdHa3f57v89yFfOg3wA\nukfoAyEsOjpaa5ausboMACGCy/sAABiC0AcAwBCEPgAAhiD0AQAwBKEPAIAheHofsDHm1gfQmwh9\nwKaYWx9Ab+PyPmBTzK0PoLcR+gAAGILQB2yKufUB9Dbu6QM2xdz6AHoboQ/YGHPrA+hNXN4HAMAQ\nhD4AAIbg8j5gGCb8AcxF6AMGYcIfwGxc3gcMwoQ/gNkIfQAADEHoAwZhwh/AbNzTBwzChD+A2Qh9\nwDBM+AOYi8v7AAAYgtAHAMAQhD4AAIYg9AEAMAShDwCAIQh9AAAMQegDAGAIQh8AAEMQ+gAAGILQ\nBwDAEIQ+AACGIPQBADAEoQ8AgCEIfQAADEHoAwBgCEIfAABDEPoAABiC0AcAwBCEPgAAhiD0AQAw\nBKEPAIAhCH0AAAxB6AMAYAhCHwAAQxD6AAAYgtAHAMAQhD4AAIYg9AEAMAShDwCAIWwX+jt27NDM\nmTPlcrnkdDp17ty5DuukpKTI6XQG/Fu7dq0F1QIAEDr+z+oCvq2trU1ZWVnKzc3V6tWrO13H4XDo\n+eef16JFi/xjgwYN6qsSAQAISbYLfbfbLUk6cuRIt+uFh4frzjvv7IuSAADoF2x3ef9G/fa3v9W9\n996ryZMnq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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10982ee50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use the original data frame for this. Let's plot NOx vs. PM10. \n",
    "# But first, let's convert these columns to a logarithmic scale, since values are so disparate.\n",
    "# We'll use numpy, a maths package, for this.\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "# Create new columns in the data frame with the log values\n",
    "df[\"log_NOx\"] = np.log(df[\"NOx\"])\n",
    "df[\"log_PM10\"] = np.log(df[\"PM10\"])\n",
    "\n",
    "scatter_plot(df, \"log_NOx\", \"log_PM10\", \"NOx vs. PM10 in Colorado\", \"NOx (log)\", \"PM10 (log)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Reference:__ [here are all the arguments that `plot()` can take](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.plot.html)  when called from a series or data frame. It includes setting axis limits and even logarithmic transformations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Go further\n",
    "\n",
    "This is just the tip of all that Matplotlib can do.\n",
    "\n",
    "[Check out the chart gallery](http://matplotlib.org/gallery.html) for inspiration and recipes for common and uncommon charts.\n",
    "\n",
    "You can also extend its design capabilities.\n",
    "\n",
    "__Fonts:__\n",
    "    \n",
    "    import matplotlib.font_manager as fm\n",
    "    title_font = fm.FontProperties(family='Bitstream Vera Sans', style='normal', size=15, weight='normal', stretch='normal')\n",
    "\n",
    "__Colors:__\n",
    "\n",
    "There are many pre-installed color palettes, or color maps.\n",
    "    \n",
    "    import matplotlib.cm as cm\n",
    "    color_map = cm.get_cmap('Pastell')\n",
    "\n",
    "[A good Jupyter Notebook](https://github.com/gboeing/urban-data-science/blob/master/12-Python-Data-Visualization/pandas-data-visualization.ipynb) that shows you how to use them.\n",
    "\n",
    "__Making maps:__\n",
    "\n",
    "[Step-by-step tutorial.](https://peak5390.wordpress.com/2012/12/08/matplotlib-basemap-tutorial-making-a-simple-map/)\n",
    "\n",
    "__More on pandas__:\n",
    "\n",
    "[An excellent introduction video.](https://www.youtube.com/watch?v=5JnMutdy6Fw)\n",
    "\n",
    "[And another one.](https://www.youtube.com/watch?v=L4Hbv4ugUWk)\n",
    "\n",
    "\n",
    "## Making interactive charts for the web\n",
    "\n",
    "[Bokeh](http://bokeh.pydata.org/en/latest/) is another visualization library for Python that creates interactive charts easily.\n",
    "\n",
    "[A good intro video.](https://www.youtube.com/watch?v=O5OvOLK-xqQ)\n"
   ]
  }
 ],
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   "display_name": "Python 2",
   "language": "python",
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    "name": "ipython",
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   "pygments_lexer": "ipython2",
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